Data scientist jobs in Stony Brook, NY

We are seeking a C++ Market Data Engineer to design and optimize ultra-low-latency feed handlers that power global trading systems. This is a high-impact role where your code directly drives real-time decision making. What You'll Do: Build high-performance feed handlers in modern C++ (14/17/20) for equities, futures, and options Optimize systems for micro/nanosecond latency with lock-free algorithms and cache-friendly design Ensure reliable data delivery with failover, gap recovery, and replay mechanisms Collaborate with researchers and engineers to align data formats for trading and simulation Instrument and test systems for continuous performance improvements What We're Looking For: 3+ years of C++ development experience (low-latency, high-throughput systems) Experience with real-time market data feeds (e.g., Bloomberg B-PIPE, CME MDP, Refinitiv, OPRA, ITCH) Strong knowledge of concurrency, memory models, and compiler optimizations Python scripting skills for testing and automation Familiarity with Docker/Kubernetes and cloud networking (AWS/GCP) is a plus

Your work will change lives. Including your own. Please note: Our offices will be closed for our annual winter break from December 22, 2025, to January 2, 2026. Our response to your application will be delayed. The Impact You'll Make As a member of Recursion's AI-driven drug discovery initiatives, you will be at the forefront of reimagining how biological knowledge is generated, stored, accessed, and reasoned upon by LLMs. You will play a key role in developing the biological reasoning infrastructure, connecting large-scale data and codebases with dynamic, agent-driven AI systems.You will be responsible for defining the architecture that grounds our agents in biological truth. This involves integrating biomedical resources to enable AI systems to reason effectively and selecting the most appropriate data retrieval strategies to support those insights. This is a highly collaborative role: you will partner with machine learning engineers, biologists, chemists, and platform teams to build the connective tissue that allows our AI agents to reason like a scientist. The ideal candidate possesses deep expertise in both core bioinformatics/cheminformatics libraries and modern GenAI frameworks (including RAG and MCP), a strong architectural vision, and the ability to translate high-potential prototypes into scalable production workflows. In this role, you will: Architect and maintain robust infrastructure to keep critical internal and external biological resources (e.g., ChEMBL, Ensembl, Reactome, proprietary assays) up-to-date and accessible to reasoning agents. Design sophisticated context retrieval strategies, choosing the most effective approach for each biological use case, whether working with structured, entity-focused data, unstructured RAG, or graph-based representations. Integrate established bioinformatics/cheminformatics libraries into a GenAI ecosystem, creating interfaces (such as via MCP) that allow agents to autonomously query and manipulate biological data. Pilot methods for tool use by LLMs, enabling the system to perform complex tasks like pathway analysis on the fly rather than relying solely on memorized weights. Develop scalable, production-grade systems that serve as the backbone for Recursion's automated scientific reasoning capabilities. Collaborate cross-functionally with Recursion's core biology, chemistry, data science and engineering teams to ensure our biological data and the reasoning engines are accurately reflecting the complexity of disease biology and drug discovery. Present technical trade-offs (e.g., graph vs. vector) to leadership and stakeholders in a clear, compelling way that aligns technical reality with product vision. The Team You'll Join You'll join a bold, agile team of scientists and engineers dedicated to building comprehensive biological maps by integrating Recursion's in-house datasets, patient data, and external knowledge layers to enable sophisticated agent-based reasoning. Within this cross-functional team, you will design and maintain the biological context and data structures that allow agents to reason accurately and efficiently. You'll collaborate closely with wet-lab biologists and core platform engineers to develop systems that are not only technically robust but also scientifically rigorous. The ideal candidate is curious about emerging AI technologies, passionate about making biological data both machine-readable and machine-understandable, and brings a strong foundation in systems biology, biomedical data analysis, and agentic AI systems. The Experience You'll Need PhD in a relevant field (Bioinformatics, Cheminformatics, Computational Biology, Computer Science, Systems Biology) with 5+ years of industry experience, or MS in a relevant field with 7+ years of experience, focusing on biological data representation and retrieval. Proficiency in utilizing major public biological databases (NCBI, Ensembl, STRING, GO) and using standard bioinformatics/cheminformatics toolkits (e.g., RDKit, samtools, Biopython). Strong skills in designing and maintaining automated data pipelines that support continuous ingestion, transformation, and refresh of biological data without manual intervention. Ability to work with knowledge graph data models and query languages (e.g., RDF, SPARQL, OWL) and translate graph-structured data into relational or other non-graph representations, with a strong judgment in evaluating trade-offs between different approaches. Competence in building and operating GenAI stacks, including RAG systems, vector databases, and optimization of context windows for large-scale LLM deployments. Hands-on expertise with agentic AI frameworks (e.g., MCP, Google ADK, LangChain, AutoGPT) and familiarity with leading LLMs (e.g., Google Gemini/Gemma) in agentic workflows, including benchmarking and evaluating agent performance on bioinformatics/cheminformatics tasks such as structure prediction, target identification, and pathway mapping. Strong Python skills and adherence to software engineering best practices, including CI/CD, Git-based version control, and modular design. Excellent cross-functional communication skills, ability to clearly explain complex architectural decisions to both scientific domain experts and technical stakeholders. Nice to Have Strong background in machine learning and deep learning, including hands-on experience with foundation models and modern neural architectures. Fine-tuning LLMs on scientific corpora for domain-specific reasoning. Integrating LLMs with experimental or proprietary assay data in live scientific workflows. Background in drug discovery and target identification. Meaningful contributions to open-source libraries, research codebases, or community-driven tools. Working Location & Compensation: This is an office-based, hybrid role in either our Salt Lake City, UT or New York City, NY offices. Employees are expected to work in the office at least 50% of the time. At Recursion, we believe that every employee should be compensated fairly. Based on the skill and level of experience required for this role, the estimated current annual base range for this role is $200,600 - $238,400. You will also be eligible for an annual bonus and equity compensation, as well as a comprehensive benefits package. #LI-DNI The Values We Hope You Share: We act boldly with integrity. We are unconstrained in our thinking, take calculated risks, and push boundaries, but never at the expense of ethics, science, or trust. We care deeply and engage directly. Caring means holding a deep sense of responsibility and respect - showing up, speaking honestly, and taking action. We learn actively and adapt rapidly. Progress comes from doing. We experiment, test, and refine, embracing iteration over perfection. We move with urgency because patients are waiting. Speed isn't about rushing but about moving the needle every day. We take ownership and accountability. Through ownership and accountability, we enable trust and autonomy-leaders take accountability for decisive action, and teams own outcomes together. We are One Recursion. True cross-functional collaboration is about trust, clarity, humility, and impact. Through sharing, we can be greater than the sum of our individual capabilities. Our values underpin the employee experience at Recursion. They are the character and personality of the company demonstrated through how we communicate, support one another, spend our time, make decisions, and celebrate collectively. More About Recursion Recursion (NASDAQ: RXRX) is a clinical stage TechBio company leading the space by decoding biology to radically improve lives. Enabling its mission is the Recursion OS, a platform built across diverse technologies that continuously generate one of the world's largest proprietary biological and chemical datasets. Recursion leverages sophisticated machine-learning algorithms to distill from its dataset a collection of trillions of searchable relationships across biology and chemistry unconstrained by human bias. By commanding massive experimental scale - up to millions of wet lab experiments weekly - and massive computational scale - owning and operating one of the most powerful supercomputers in the world, Recursion is uniting technology, biology and chemistry to advance the future of medicine. Recursion is headquartered in Salt Lake City, where it is a founding member of BioHive, the Utah life sciences industry collective. Recursion also has offices in Toronto, Montréal, New York, London, Oxford area, and the San Francisco Bay area. Learn more at ****************** or connect on X (formerly Twitter) and LinkedIn. Recursion is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected under applicable federal, state, local, or provincial human rights legislation. Accommodations are available on request for candidates taking part in all aspects of the selection process. Recruitment & Staffing Agencies: Recursion Pharmaceuticals and its affiliate companies do not accept resumes from any source other than candidates. The submission of resumes by recruitment or staffing agencies to Recursion or its employees is strictly prohibited unless contacted directly by Recursion's internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Recursion, and Recursion will not owe any referral or other fees. Our team will communicate directly with candidates who are not represented by an agent or intermediary unless otherwise agreed to prior to interviewing for the job.

About the Role We believe that the best decisions are backed by data. We are seeking a curious and analytical Data Scientist to champion our data -driven culture. In this role, you will act as a bridge between technical data and business strategy. You will mine massive datasets, build predictive models, and-most importantly-tell the story behind the numbers to help our leadership team make smarter choices. You are perfect for this role if you are as comfortable with SQL queries as you are with slide decks. ### What You Will Do Exploratory Analysis: Dive deep into raw data to discover trends, patterns, and anomalies that others miss. Predictive Modeling: Build and test statistical models (Regression, Time -series, Clustering) to forecast business outcomes and customer behavior. Data Visualization: Create clear, impactful dashboards using Tableau, PowerBI, or Python libraries (Matplotlib/Seaborn) to visualize success metrics. Experimentation: Design and analyze A/B tests to optimize product features and marketing campaigns. Data Cleaning: Work with Data Engineers to clean and structure messy data for analysis. Strategy: Present findings to stakeholders, translating complex math into clear, actionable business recommendations. Requirements Experience: 2+ years of experience in Data Science or Advanced Analytics. The Toolkit: Expert proficiency in Python or R for statistical analysis. Data Querying: Advanced SQL skills are non -negotiable (Joins, Window Functions, CTEs). Math Mindset: Strong grasp of statistics (Hypothesis testing, distributions, probability). Visualization: Ability to communicate data visually using Tableau, PowerBI, or Looker. Communication: Excellent verbal and written skills; you can explain a p -value to a non -technical manager. ### Preferred Tech Stack (Keywords) Languages: Python (Pandas, NumPy), R, SQL Viz Tools: Tableau, PowerBI, Looker, Plotly Machine Learning: Scikit -learn, XGBoost (applied to business problems) Big Data: Spark, Hadoop, Snowflake Benefits Salary Range: $50,000 - $180,000 USD / year (Commensurate with location and experience) Remote Friendly: Work from where you are most productive. Learning Budget: Stipend for data courses (Coursera, DataCamp) and books.

Job Description The Sales Data Scientist will use data analytics and statistical techniques to generate insights that support sales performance and revenue growth. This role focuses on building and improving reporting tools, analyzing data, and providing actionable recommendations to help the sales organization make informed decisions. Key Responsibilities · Data Analysis & Reporting · Analyze sales data to identify trends, patterns, and opportunities. · Create and maintain dashboards and reports for Sales and leadership teams. · Support root-cause analysis and process improvement initiatives. · Sales Insights · Provide data-driven recommendations for pricing, discount strategies, and sales funnel optimization. · Assist in segmentation analysis to identify key customer groups and markets. · Collaboration · Work closely with Sales, Marketing, Finance, and Product teams to align analytics with business needs. · Present findings in clear, actionable formats to stakeholders. · Data Infrastructure · Ensure data accuracy and integrity across reporting tools. · Help automate reporting processes for efficiency and scalability. Required Qualifications: · 2-4 years of experience in a data analytics or sales operations role. · Strong Excel skills (pivot tables, formulas, data analysis). · Bachelor's degree in Mathematics, Statistics, Economics, Data Science, or related field-or equivalent experience. Preferred Qualifications: · Familiarity with Python, R, SQL, and data visualization tools (e.g., Power BI). · Experience leveraging AI/ML tools and platforms (e.g., predictive analytics, natural language processing, automated insights). · Experience with CRM systems (Salesforce) and marketing automation platforms. · Strong analytical and problem-solving skills with attention to detail. · Ability to communicate insights clearly to non-technical audiences. · Collaborative mindset and willingness to learn new tools and techniques. Why Apply to Drive DeVilbiss… Competitive Benefits, Paid Time Off, 401(k) Savings Plan Pursuant to New York law, Drive Medical provides a salary range in job advertisements. The salary range for this role is $95,000.00 to $125,000.00 per year. Actual salaries may vary depending on factors such as the applicant's experience, specialization, education, as well as the company's requirements. The provided salary range does not include bonuses, incentives, differential pay, or other forms of compensation or benefits which may be offered to the applicant, if eligible according to the company's policies. Drive Medical is an Equal Opportunity Employer and provides equal employment opportunities to all employees and applicants for employment. Drive Medical strictly prohibits and does not tolerate discrimination against employees, applicants, or any other covered person because of race, color, religion, gender, sexual orientation, gender identity, pregnancy and/or parental status, national origin, age, disability status, protected veteran status, genetic information (including family medical history), or any other characteristic protected by federal, state, or local law. Drive Medical complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities.

Description & Requirements We now have an exciting opportunity for a Principal Data Scientist to join the Maximus AI Accelerator supporting both the enterprise and our clients. We are looking for an accomplished hands-on individual contributor and team player to be a part of the AI Accelerator team. You will be responsible for architecting and optimizing scalable, secure AI systems and integrating AI models in production using MLOps best practices, ensuring systems are resilient, compliant, and efficient. This role requires strong systems thinking, problem-solving abilities, and the capacity to manage risk and change in complex environments. Success depends on cross-functional collaboration, strategic communication, and adaptability in fast-paced, evolving technology landscapes. This position will be focused on strategic company-wide initiatives but will also play a role in project delivery and capture solutioning (i.e., leaning in on existing or future projects and providing solutioning to capture new work.) This position requires occasional travel to the DC area for client meetings. Essential Duties and Responsibilities: - Make deep dives into the data, pulling out objective insights for business leaders. - Initiate, craft, and lead advanced analyses of operational data. - Provide a strong voice for the importance of data-driven decision making. - Provide expertise to others in data wrangling and analysis. - Convert complex data into visually appealing presentations. - Develop and deploy advanced methods to analyze operational data and derive meaningful, actionable insights for stakeholders and business development partners. - Understand the importance of automation and look to implement and initiate automated solutions where appropriate. - Initiate and take the lead on AI/ML initiatives as well as develop AI/ML code for projects. - Utilize various languages for scripting and write SQL queries. Serve as the primary point of contact for data and analytical usage across multiple projects. - Guide operational partners on product performance and solution improvement/maturity options. - Participate in intra-company data-related initiatives as well as help foster and develop relationships throughout the organization. - Learn new skills in advanced analytics/AI/ML tools, techniques, and languages. - Mentor more junior data analysts/data scientists as needed. - Apply strategic approach to lead projects from start to finish; Job-Specific Minimum Requirements: - Develop, collaborate, and advance the applied and responsible use of AI, ML and data science solutions throughout the enterprise and for our clients by finding the right fit of tools, technologies, processes, and automation to enable effective and efficient solutions for each unique situation. - Contribute and lead the creation, curation, and promotion of playbooks, best practices, lessons learned and firm intellectual capital. - Contribute to efforts across the enterprise to support the creation of solutions and real mission outcomes leveraging AI capabilities from Computer Vision, Natural Language Processing, LLMs and classical machine learning. - Contribute to the development of mathematically rigorous process improvement procedures. - Maintain current knowledge and evaluation of the AI technology landscape and emerging. developments and their applicability for use in production/operational environments. Minimum Requirements - Bachelor's degree in related field required. - 10-12 years of relevant professional experience required. Job-Specific Minimum Requirements: - 10+ years of relevant Software Development + AI / ML / DS experience. - Professional Programming experience (e.g. Python, R, etc.). - Experience in two of the following: Computer Vision, Natural Language Processing, Deep Learning, and/or Classical ML. - Experience with API programming. - Experience with Linux. - Experience with Statistics. - Experience with Classical Machine Learning. - Experience working as a contributor on a team. Preferred Skills and Qualifications: - Masters or BS in quantitative discipline (e.g. Math, Physics, Engineering, Economics, Computer Science, etc.). - Experience developing machine learning or signal processing algorithms: - Ability to leverage mathematical principles to model new and novel behaviors. - Ability to leverage statistics to identify true signals from noise or clutter. - Experience working as an individual contributor in AI. - Use of state-of-the-art technology to solve operational problems in AI and Machine Learning. - Strong knowledge of data structures, common computing infrastructures/paradigms (stand alone and cloud), and software engineering principles. - Ability to design custom solutions in the AI and Advanced Analytics sphere for customers. This includes the ability to scope customer needs, identify currently existing technologies, and develop custom software solutions to fill any gaps in available off the shelf solutions. - Ability to build reference implementations of operational AI & Advanced Analytics processing solutions. Background Investigations: - IRS MBI - Eligibility #techjobs #VeteransPage EEO Statement Maximus is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, age, national origin, disability, veteran status, genetic information and other legally protected characteristics. Pay Transparency Maximus compensation is based on various factors including but not limited to job location, a candidate's education, training, experience, expected quality and quantity of work, required travel (if any), external market and internal value analysis including seniority and merit systems, as well as internal pay alignment. Annual salary is just one component of Maximus's total compensation package. Other rewards may include short- and long-term incentives as well as program-specific awards. Additionally, Maximus provides a variety of benefits to employees, including health insurance coverage, life and disability insurance, a retirement savings plan, paid holidays and paid time off. Compensation ranges may differ based on contract value but will be commensurate with job duties and relevant work experience. An applicant's salary history will not be used in determining compensation. Maximus will comply with regulatory minimum wage rates and exempt salary thresholds in all instances. Accommodations Maximus provides reasonable accommodations to individuals requiring assistance during any phase of the employment process due to a disability, medical condition, or physical or mental impairment. If you require assistance at any stage of the employment process-including accessing job postings, completing assessments, or participating in interviews,-please contact People Operations at **************************. Minimum Salary $ 156,740.00 Maximum Salary $ 234,960.00

RISE Data Scientist Reports to: Monitoring, Evaluation, and Learning Manager Salary: Competitive and commensurate with experience Please note: Due to the upcoming holidays, application review for this position will begin the first week of January. Applicants can expect outreach by the end of the week of January 5. Overview: The RISE Network's mission is to ensure all high school students graduate with a plan and the skills and confidence to achieve college and career success. Founded in 2016, RISE partners with public high schools to lead networks where communities work together to use data to learn and improve. Through its core and most comprehensive network, RISE partners with nine high schools and eight districts, serving over 13,000 students in historically marginalized communities. RISE high schools work together to ensure all students experience success as they transition to, through, and beyond high school by using data to pinpoint needs, form hypotheses, and pursue ideas to advance student achievement. Partner schools have improved Grade 9 promotion rates by nearly 20 percentage points, while also decreasing subgroup gaps and increasing schoolwide graduation and college access rates. In 2021, the RISE Network was honored to receive the Carnegie Foundation's annual Spotlight on Quality in Continuous Improvement recognition. Increasingly, RISE is pursuing opportunities to scale its impact through research publications, consulting partnerships, professional development experiences, and other avenues to drive excellent student outcomes. Position Summary and Essential Job Functions: The RISE Data Scientist will play a critical role in leveraging data to support continuous improvement, program evaluation, and research, enhancing the organization's evidence-based learning and decision-making. RISE is seeking a talented and motivated individual to design and conduct rigorous quantitative analyses to assess the outcomes and impacts of programs. The ideal candidate is an experienced analyst who is passionate about using data to drive social change, with strong skills in statistical modeling, data visualization, and research design. This individual will also lead efforts to monitor and analyze organization-wide data related to mission progress and key performance indicators (KPIs), and communicate these insights in ways that inspire improvement and action. This is an exciting opportunity for an individual who thrives in an entrepreneurial environment and is passionate about closing opportunity gaps and supporting the potential of all students, regardless of life circumstances. The role will report to the Monitoring, Evaluation, and Learning (MEL) Manager and sit on the MEL team. Responsibilities include, but are not limited to: 1. Research and Evaluation (30%) Collaborate with MEL and network teams to design and implement rigorous process, outcome, and impact evaluations. Lead in the development of data collection tools and survey instruments. Manage survey data collection, reporting, and learning processes. Develop RISE learning and issue briefs supported by quantitative analysis. Design and implement causal inference approaches where applicable, including quasi-experimental designs. Provide technical input on statistical analysis plans, monitoring frameworks, and indicator selection for network programs. Translate complex findings into actionable insights and policy-relevant recommendations for non-technical audiences. Report data for RISE leadership and staff, generating new insights to inform program design. Create written reports, presentations, publications, and communications pieces. 2. Quantitative Analysis and Statistical Modeling (30%) Clean, transform, and analyze large and complex datasets from internal surveys, the RISE data warehouse, and external data sources such as the National Student Clearinghouse (NSC). Conduct exploratory research that informs organizational learning. Lead complex statistical analyses using advanced methods (regression modeling, propensity score matching, difference in differences analysis, time-series analysis, etc). Contribute to data cleaning and analysis for key performance indicator reporting. Develop processes that support automation of cleaning and analysis for efficiency. Develop and maintain analytical code and workflows to ensure reproducibility. 3. Data Visualization and Tool-building (30%) Work closely with non-technical stakeholders to understand the question(s) they are asking and the use cases they have for specific data visualizations or tools Develop well-documented overviews and specifications for new tools. Create clear, compelling data visualizations and dashboards. Collaborate with Data Engineering to appropriately and sustainably source data for new tools. Manage complex projects to build novel and specific tools for internal or external stakeholders. Maintain custom tools for the duration of their usefulness, including by responding to feedback and requests from project stakeholders. 4. Data Governance and Quality Assurance (10%) Support data quality assurance protocols and standards across the MEL team. Ensure compliance with data protection, security, and ethical standards. Maintain organized, well-documented code and databases. Collaborate with the Data Engineering team to maintain RISE MEL data infrastructure. Qualifications Master's degree (or PhD) in statistics, economics, quantitative social sciences, public policy, data science, or related field. Minimum of 3 years of professional experience conducting statistical analysis and managing large datasets. Advanced proficiency in R, Python, or Stata for data analysis and modeling. Experience designing and implementing quantitative research and evaluation studies. Strong understanding of inferential statistics, experimental and quasi-experimental methods, and sampling design. Strong knowledge of survey data collection tools such as Key Surveys, Google Forms, etc. Excellent data visualization and communication skills Experience with data visualization tools; strong preference for Tableau. Ability to translate complex data into insights for diverse audiences, including non-technical stakeholders. Ability to cultivate relationships and earn credibility with a diverse range of stakeholders. Strong organizational and project management skills. Strong sense of accountability and responsibility for results. Ability to work in an independent and self-motivated manner. Demonstrated proficiency with Google Workspace. Commitment to equity, ethics, and learning in a nonprofit or mission-driven context. Positive attitude and willingness to work in a collaborative environment. Strong belief that all students can learn and achieve at high levels. Preferred Experience working on a monitoring, evaluation, and learning team. Familiarity with school data systems and prior experience working in a school, district, or similar K-12 educational context preferred. Experience working with survey data (e.g., DHS, LSMS), administrative datasets, or real-time digital data sources. Working knowledge of data engineering or database management (SQL, cloud-based platforms). Salary Range $85k - $105k Most new hires' salaries fall within the first half of the range, allowing team members to grow in their roles. For those who already have significant and aligned experiences at the same level as the role, placement may be at the higher end of the range. The Connecticut RISE Network is an equal opportunity employer and welcomes candidates from diverse backgrounds.

About Us Bexorg is revolutionizing drug discovery by restoring molecular activity in postmortem human brains. Through our BrainEx platform, we directly experiment on functionally preserved human brain tissue, creating enormous high-fidelity molecular datasets that fuel AI-driven breakthroughs in treating CNS diseases. We are looking for a Junior Data Scientist to join our team and dive into this one-of-a-kind data. In this onsite role, you will work at the intersection of computational biology and machine learning, helping analyze high-dimensional brain data and uncover patterns that could lead to the next generation of CNS therapeutics. This is an ideal opportunity for a recent graduate or early-career scientist to grow in a fast-paced, mission-driven environment. The Job Data Analysis & Exploration: Work with large-scale molecular datasets from our BrainEx experiments - including transcriptomic, proteomic, and metabolic data. Clean, transform, and explore these high-dimensional datasets to understand their structure and identify initial insights or anomalies. Collaborative Research Support: Collaborate closely with our life sciences, computational biology and deep learning teams to support ongoing research. You will help biologists interpret data results and assist machine learning researchers in preparing data for modeling, ensuring that domain knowledge and data science intersect effectively. Machine Learning Model Execution: Run and tune machine learning and deep learning models on real-world central nervous system (CNS) data. You'll help set up experiments, execute training routines (for example, using scikit-learn or PyTorch models), and evaluate model performance to extract meaningful patterns that could inform drug discovery. Statistical Insight Generation: Apply statistical analysis and visualization techniques to derive actionable insights from complex data. Whether it's identifying gene expression patterns or correlating molecular changes with experimental conditions, you will contribute to turning data into scientific discoveries. Reporting & Communication: Document your analysis workflows and results in clear reports or dashboards. Present findings to the team, highlighting key insights and recommendations. You will play a key role in translating data into stories that drive decision-making in our R&D efforts. Qualifications and Skills: Strong Python Proficiency: Expert coding skills in Python and deep familiarity with the standard data science stack. You have hands-on experience with NumPy, pandas, and Matplotlib for data manipulation and visualization; scikit-learn for machine learning; and preferably PyTorch (or similar frameworks like TensorFlow) for deep learning tasks. Educational Background: A Bachelor's or Master's degree in Data Science, Computer Science, Computational Biology, Bioinformatics, Statistics, or a related field. Equivalent practical project experience or internships in data science will also be considered. Machine Learning Knowledge: Solid understanding of machine learning fundamentals and algorithms. Experience developing or applying models to real or simulated datasets (through coursework or projects) is expected. Familiarity with high-dimensional data techniques or bioinformatics methods is a plus. Analytical & Problem-Solving Skills: Comfortable with statistics and data analysis techniques for finding signals in noisy data. Able to break down complex problems, experiment with solutions, and clearly interpret the results. Team Player: Excellent communication and collaboration skills. Willingness to learn from senior scientists and ability to contribute effectively in a multidisciplinary team that includes biologists, data engineers, and AI researchers. Motivation and Curiosity: Highly motivated, with an evident passion for data-driven discovery. You are excited by Bexorg's mission and eager to take on challenging tasks - whether it's mastering a new analysis method or digging into scientific literature - to push our research forward. Local to New Haven, CT preferred. No relocation offered for this position. Bexorg is an equal opportunity employer. We strive to create a supportive and inclusive workplace where contributions are valued and celebrated, and our employees thrive by being themselves and are inspired to do their best work. We seek applicants of all backgrounds and identities, across race, color, ethnicity, national origin or ancestry, citizenship, religion, sex, sexual orientation, gender identity or expression, veteran status, marital status, pregnancy or parental status, or disability. Applicants will not be discriminated against based on these or other protected categories or social identities. Bexorg will also consider for employment qualified applicants with criminal histories in a manner consistent with applicable federal, state and local law.

Atlas Air is seeking a detail-oriented and analytical Network Planning Analyst to help optimize our global cargo network. This role plays a critical part in the 2-year to 11-day planning window, driving insights that enable operational teams to execute the most efficient and reliable schedules. The successful candidate will provide actionable analysis on network delays, utilization trends, and operating performance, build models and reports to govern network operating parameters, and contribute to the development and implementation of software optimization tools that improve reliability and streamline planning processes. This position requires strong analytical skills, a proactive approach to problem-solving, and the ability to translate data into operational strategies that protect service quality and maximize network efficiency. Responsibilities * Analyze and Monitor Network Performance * Track and assess network delays, capacity utilization, and operating constraints to identify opportunities for efficiency gains and reliability improvements. * Develop and maintain key performance indicators (KPIs) for network operations and planning effectiveness. * Modeling & Optimization * Build and maintain predictive models to assess scheduling scenarios and network performance under varying conditions. * Support the design, testing, and implementation of software optimization tools to enhance operational decision-making. * Reporting & Governance * Develop periodic performance and reliability reports for customers, assisting in presentation creation * Produce regular and ad hoc reports to monitor compliance with established operating parameters. * Establish data-driven processes to govern scheduling rules, protect operational integrity, and ensure alignment with reliability targets. * Cross-Functional Collaboration * Partner with Operations, Planning, and Technology teams to integrate analytics into network planning and execution. * Provide insights that inform schedule adjustments, fleet utilization, and contingency planning. * Innovation & Continuous Improvement * Identify opportunities to streamline workflows and automate recurring analyses. * Contributes to the development of new planning methodologies and tools that enhance decision-making and operational agility. Qualifications * Proficiency in SQL (Python and R are a plus) for data extraction and analysis; experience building decision-support tools, reporting tools dashboards (e.g., Tableau, Power BI) * Bachelor's degree required in Industrial Engineering, Operations Research, Applied Mathematics, Data Science or related quantitative discipline or equivalent work experience. * 5+ years of experience in strategy, operations planning, finance or continuous improvement, ideally with airline network planning * Strong analytical skills with experience in statistical analysis, modeling, and scenario evaluation. * Strong problem-solving skills with the ability to work in a fast-paced, dynamic environment. * Excellent communication skills with the ability to convey complex analytical findings to non-technical stakeholders. * A proactive, solution-focused mindset with a passion for operational excellence and continuous improvement. * Knowledge of operations, scheduling, and capacity planning, ideally in airlines, transportation or other complex network operations Salary Range: $131,500 - $177,500 Financial offer within the stated range will be based on multiple factors to include but not limited to location, relevant experience/level and skillset. The Company is an Equal Opportunity Employer. It is our policy to afford equal employment opportunity to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, national origin, citizenship, place of birth, age, disability, protected veteran status, gender identity or any other characteristic or status protected by applicable in accordance with federal, state and local laws. If you'd like more information about your EEO rights as an applicant under the law, please download the available EEO is the Law document at ****************************************** To view our Pay Transparency Statement, please click here: Pay Transparency Statement "Know Your Rights: Workplace Discrimination is Illegal" Poster The "EEO Is The Law" Poster

Howden Re is the global reinsurance broker and risk, capital & strategic advisor focused on relentless innovation & superior analytics for top client service. About Role This is a Mid-level position and will reside within the Actuarial team. We expect this person to work successfully across Analytics, Actuarial, and Broking functions providing the full suite of actuarial work in support of reinsurance placements for clients. You will be joining an experienced analytics team that produces quality solutions in a collegial, casual, and results-driven environment. Responsibilities | Support: Traditional LR analysis, experience/exposure rating, stochastic modelling, etc Present analyses in clear terms appropriate to the audience Provide value-added service to clients as needed Market research and development & assist senior actuaries with industry studies A high priority will be the development & programming of various tools to aid in streamlining workflow and helping Howden Re fully utilize data Interpersonal | Communication | Teamwork: Willingness to be part of Howden Re's “team first” culture Keen ability to take initiative Sets effective priorities and handles multiple projects under tight timeframes Responds constructively to different viewpoints, changing priorities, new conditions Works well in teams with colleagues of various backgrounds Shares knowledge, opinions and insights in constructive manner Offers to help others without prompting, & assists others in learning Qualifications: ACAS or FCAS required Bachelor's degree from reputable university; advanced degree a huge plus 7-15 years of experience in the (re)insurance industry Able to apply advanced mathematical / actuarial concepts and techniques Skilled in using Microsoft Excel Software experience with R, VBA, Python Proven track record of hard work, client success, and innovation Legally authorized to work in the United States The expected base salary range for this role is $225,000-300,000. The base salary range is based on level of relevant experience and location and does not include other types of compensation such as discretionary bonus or benefits.

EXCLUSIVE! Highly visible Regional Chief Actuary opportunity with Multinational Insurance leader, offering the chance to lead as Appointed Actuary for U. S. legal entities, sign SAOs, and serve as a trusted advisor to the Global Chief Actuary. Influential role leads actuarial strategy, reserve governance, valuation, and financial reporting while ensuring regulatory compliance across North America. With extensive interaction among worldwide leaders and business partners, the Chief Actuary fosters collaboration across diverse regions by leveraging both cultural and technical expertise. Seeking a relationship-oriented ACAS/FCAS with deep Reserving and Casualty market expertise to guide and inspire a high-performing actuarial team with confidence and integrity. Base salary up to $315K plus a robust benefits package.

Join the fintech powerhouse redefining how the world invests in private markets. iCapital is a global leader in alternative investments, trusted by financial advisors, wealth managers, asset managers, and industry innovators worldwide. With $999.73 billion in assets serviced globally-including $272.1 billion in alternative platform assets-we empower over 3,000 wealth management firms and 118,000 financial professionals to deliver cutting-edge alternative investment solutions. This summer, become part of a dynamic team where your ideas matter. Make a meaningful impact, accelerate your professional growth, and help push the boundaries of what's possible at the intersection of technology and finance. Key features of our Summer 2026 Internship: Become a key member of the iCapital team, driving initiatives, contributing to projects, and potentially jumpstart your career with us after graduation. Immerse yourself in an inclusive company culture where we create a sense of belonging for everyone. Gain exclusive access to the AltsEdge Certificate Program, our award-winning alternative investments education curriculum for wealth managers. Attend recurring iLearn seminars and platform demos where you will learn the latest about our products. Participate in an intern team project, culminating in an end-of-summer presentation to a panel of senior executives. Join senior executive speaker seminars that provide career development, guidance, and access to the leaders at iCapital. About the role: The Data Solutions department provides a reporting service that leverages top-tier third-party reporting tools to assist UHNW clients in identifying opportunities and risks within their portfolios. Through collaborations with leading technology platforms, we curate reports that offer insightful, consolidated, real-time views of all assets and liabilities, detailing what they are, who holds them, how ownership is divided, how they're invested, and how they're performing. These reports are strategically designed to uncover opportunities and highlight financial risks. Learn and leverage financial reporting and data aggregation tools: Conduct account level reconciliation. Provide accurate and timely statements and data entry. Work with internal teams to resolve data issues. Generate Ad Hoc reports as needed. Work with the team to prioritize individual and communal work to ensure all projects are completed on time and to detailed specifications. Valued qualities and key skills: Highly inquisitive, collaborative, and a creative problem solver Possess foundational knowledge of and/or genuine interest in the financial markets Able to thrive in a fast-paced environment Able to adapt to new responsibilities and manage competing priorities Technologically proficient in Microsoft Office (Excel, PowerPoint) Strong verbal and written communication skills What we offer: Outings with iCapital team members and fellow interns to build connections and grow your network. Corporate culture and volunteer activities in support of the communities where we live and work. Rooftop Happy Hours showcasing our impressive views of NYC. Eligibility: A rising junior or senior in a U.S. college/university bachelor's degree program Must be available to work the duration of the program from June 8th through August 7th to be eligible Committed to working five days a week in the Stamford office for the entire duration of the internship Authorized to work in the United States* *We are unable to offer any type of employment-based immigration sponsorship for this program Pay Rate: $31.00/hour + relocation stipend and transportation stipend iCapital in the Press: We are innovating at the intersection of technology and investment opportunity, but don't take our word for it. Here's what others are saying about us: Two consecutive years on the CNBC World's Top Fintech Companies list Two consecutive years listed in Top 100 Fastest Growing Financial Services Companies Four-time winner of the Money Management Institute/Barron's Solutions Provider of the Year For additional information on iCapital, please visit **************************************** Twitter: @icapitalnetwork | LinkedIn: ***************************************************** | Awards Disclaimer: ****************************************/recognition/

OPEN JOB: Data Engineer w AWS services such as AWS Glue, Lambda, Athena, Step Functions, and Lake **HYBRID - This candidate will work on site 2-3X per week in Ridgefield CT location SALARY: $140,000 to $185,000 2 Openings NOTE: CANDIDATE MUST BE US CITIZEN OR GREEN CARD HOLDER We are seeking a highly skilled and experienced Data Engineer to design, build, and maintain our scalable and robust data infrastructure on a cloud platform. In this pivotal role, you will be instrumental in enhancing our data infrastructure, optimizing data flow, and ensuring data availability. You will be responsible for both the hands-on implementation of data pipelines and the strategic design of our overall data architecture. Seeking a candidate with hands-on experience with AWS services such as AWS Glue, Lambda, Athena, Step Functions, and Lake, Proficiency in Python and SQL and DevOps/CI/CD experience Duties & Responsibilities Design, develop, and maintain scalable data pipelines and ETL processes to support data integration and analytics. Collaborate with data architects, modelers and IT team members to help define and evolve the overall cloud-based data architecture strategy, including data warehousing, data lakes, streaming analytics, and data governance frameworks Collaborate with data scientists, analysts, and other business stakeholders to understand data requirements and deliver solutions. Optimize and manage data storage solutions (e.g., S3, Snowflake, Redshift) ensuring data quality, integrity, security, and accessibility. Implement data quality and validation processes to ensure data accuracy and reliability. Develop and maintain documentation for data processes, architecture, and workflows. Monitor and troubleshoot data pipeline performance and resolve issues promptly. Consulting and Analysis: Meet regularly with defined clients and stakeholders to understand and analyze their processes and needs. Determine requirements to present possible solutions or improvements. Technology Evaluation: Stay updated with the latest industry trends and technologies to continuously improve data engineering practices. Requirements Cloud Expertise: Expert-level proficiency in at least one major cloud platform (AWS, Azure, or GCP) with extensive experience in their respective data services (e.g., AWS S3, Glue, Lambda, Redshift, Kinesis; Azure Data Lake, Data Factory, Synapse, Event Hubs; GCP BigQuery, Dataflow, Pub/Sub, Cloud Storage); experience with AWS data cloud platform preferred SQL Mastery: Advanced SQL writing and optimization skills. Data Warehousing: Deep understanding of data warehousing concepts, Kimball methodology, and various data modeling techniques (dimensional, star/snowflake schemas). Big Data Technologies: Experience with big data processing frameworks (e.g., Spark, Hadoop, Flink) is a plus. Database Systems: Experience with relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB, Cassandra). DevOps/CI/CD: Familiarity with DevOps principles and CI/CD pipelines for data solutions. Hands-on experience with AWS services such as AWS Glue, Lambda, Athena, Step Functions, and Lake Formation Proficiency in Python and SQL Desired Skills, Experience and Abilities 4+ years of progressive experience in data engineering, with a significant portion dedicated to cloud-based data platforms. ETL/ELT Tools: Hands-on experience with ETL/ELT tools and orchestrators (e.g., Apache Airflow, Azure Data Factory, AWS Glue, dbt). Data Governance: Understanding of data governance, data quality, and metadata management principles. AWS Experience: Ability to evaluate AWS cloud applications, make architecture recommendations; AWS solutions architect certification (Associate or Professional) is a plus Familiarity with Snowflake Knowledge of dbt (data build tool) Strong problem-solving skills, especially in data pipeline troubleshooting and optimization If you are interested in pursuing this opportunity, please respond back and include the following: Full CURRENT Resume Required compensation Contact information Availability Upon receipt, one of our managers will contact you to discuss in full STEPHEN FLEISCHNER Recruiting Manager INTERMEDIA GROUP, INC. EMAIL: *******************************

Shape Your Future With Us Genesis Management and Insurance Services Corporation (Genesis) is a premier alternative risk transfer provider, offering innovative solutions for the unique needs of public entity and education clients. Genesis takes pride in being a long-term thought partner and provider of insurance and reinsurance to public sector, K-12 and higher education self-insured individual risks, pools and trusts for over 30 years. Genesis is a wholly-owned subsidiary of General Re Corporation, a subsidiary of Berkshire Hathaway Inc. General Re Corporation is a holding company for global reinsurance and related operations with more than 2,000 employees worldwide. Our first-class financial security receives the highest financial strength ratings. Genesis currently offers an excellent opportunity for a P&C Commercial Insurance Data Analytics Intern based in our Stamford office. This opportunity is for available for Summer 2026 (July-August). This is a hybrid role. Role Description Join Genesis' Actuarial Pricing Unit for an immersive 8-week internship during Summer 2026. This program is designed to provide hands-on experience in actuarial pricing, data analytics, and research. Interns will work on real-world projects that combine technical skills with critical thinking to support pricing strategies and risk assessment. You will: * Gain exposure to actuarial concepts, insurance industry practices, and pricing methodologies. * Work with advanced tools and technologies, including R, SQL, Excel, and cloud-based data platforms. * Collect, clean, and structure data for analysis and modeling. * Perform exploratory analysis to identify trends and support decision-making. * Conduct research to evaluate industry developments and their impact on pricing. * Document processes and communicate findings clearly to technical and non-technical audiences. This internship is ideal for students who are analytical, detail-oriented, and eager to apply data-driven approaches to solve complex business challenges. You'll develop practical skills in data engineering, quantitative analysis, and research while collaborating with experienced professionals in a dynamic environment. Role Qualifications and Experience Required Skill Set * Technical Skills - * Experience with R and advanced skills in Excel. * Familiar with SQL and cloud-based data warehouses(e.g., Google BigQuery). * Special consideration for Postgres or spatial analytics. * Alternative data analysis and modeling tool like Python may be acceptable. * Data Collection & Engineering - Familiarity with gathering raw data, cleaning it, standardizing formats, and building structured datasets. * Research Skills - Ability to search, evaluate, and synthesize information from diverse online sources. * Organization & Documentation - Strong ability to organize information, track data sources, and document the research process. * Analytical & Quantitative Skills - Comfort with exploratory analysis, identifying trends, and supporting basic modeling work. * Critical Thinking - Ability to connect data insights with social, legal, and environmental developments. * Communication Skills - Capability to clearly explain findings to audiences with limited technical or subject-matter background. Salary Range $22.00 - $25.00 per hour The annual base salary range posted represents a broad range of salaries around the US and is subject to many factors including but not limited to credentials, education, experience, geographic location, job responsibilities, performance, skills and/or training. Our Corporate Headquarters Address General Reinsurance Corporation 400 Atlantic Street, 9th Floor Stamford, CT 06901 (US) At General Re Corporation, we celebrate diversity and are committed to creating an inclusive environment for all employees. It is the General Re Corporation's continuing policy to afford equal employment opportunity to all employees and applicants for employment without regard to race, color, sex (including childbirth or related medical conditions), religion, national origin or ancestry, age, past or present disability , marital status, liability for service in the armed forces, veterans' status, citizenship, sexual orientation, gender identity, or any other characteristic protected by applicable law. In addition, Gen Re provides reasonable accommodation for qualified individuals with disabilities in accordance with the Americans with Disabilities Act.

Employment Type: Full-time employment - no consulting or corp to corp Salary Range: $140K - $185K + bonus Visa restrictions: US Citizen or Green Card only. This role isn't eligible for H-1B, TN, F1 or OPT Overview We are looking for a hands-on Data Engineer to design, build, and maintain scalable data platforms and pipelines in a modern cloud environment. You will play a key role in shaping our data architecture, optimizing data flow, and ensuring data quality and availability across the organization. This role offers the opportunity to contribute directly to meaningful work that supports the development and delivery of life-changing products. You will collaborate with global teams and be part of a culture that values impact, growth, balance, and well-being. What You'll Do Design, build, and optimize data pipelines and ETL/ELT workflows to support analytics and reporting. Partner with architects and engineering teams to define and evolve our cloud-based data architecture, including data lakes, data warehouses, and streaming data platforms. Work closely with data scientists, analysts, and business partners to understand requirements and deliver reliable, reusable data solutions. Develop and maintain scalable data storage solutions (e.g., AWS S3, Redshift, Snowflake) with a focus on performance, reliability, and security. Implement data quality checks, validation processes, and metadata documentation. Monitor, troubleshoot, and improve pipeline performance and workflow efficiency. Stay current on industry trends and recommend new technologies and approaches. Qualifications Data Engineer (Mid-Level) Strong understanding of data integration, data modeling, and SDLC. Experience working on project teams and delivering within Agile environments. Hands-on experience with AWS data services (e.g., Glue, Lambda, Athena, Step Functions, Lake Formation). Associate degree + 8 years experience, or Bachelor's + 4 years, or Master's + 2 years. Or Associate degree + 4 years experience, or Bachelor's + 2 years, or Master's + 1 year experience. Expert-level proficiency in at least one major cloud platform (AWS preferred). Advanced SQL and strong understanding of data warehousing and data modeling (Kimball/star schema). Experience with big data processing (e.g., Spark, Hadoop, Flink) is a plus. Experience with relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB, Cassandra). Familiarity with CI/CD pipelines and DevOps principles. Proficiency in Python and SQL (required). Desired Skills Experience with ETL/ELT tools (e.g., Airflow, dbt, AWS Glue, ADF). Understanding of data governance and metadata management. Experience with Snowflake. AWS certification is a plus. Strong problem-solving skills and ability to troubleshoot pipeline performance issues.

Job Description Our Client A fast moving and venture backed advertising technology startup based in San Francisco. They have raised twelve million dollars in funding and are transforming how business to business marketers reach their ideal customers. Their identity resolution technology blends business and consumer signals to convert static audience lists into high match and cross channel segments without the use of cookies. By transforming first party and third party data into precision targetable audiences across platforms such as Meta, Google and YouTube, they enable marketing teams to reach higher match rates, reduce wasted advertising spend and accelerate pipeline growth. With a strong understanding of how business buyers behave in channels that have traditionally been focused on business to consumer activity, they are redefining how business brands scale demand generation and account based efforts. About Us Catalyst Labs is a leading talent agency with a specialized vertical in Applied AI, Machine Learning, and Data Science. We stand out as an agency thats deeply embedded in our clients recruitment operations. We collaborate directly with Founders, CTOs, and Heads of AI in those themes who are driving the next wave of applied intelligence from model optimization to productized AI workflows. We take pride in facilitating conversations that align with your technical expertise, creative problem-solving mindset, and long-term growth trajectory in the evolving world of intelligent systems. Location: San Francisco Work type: Full Time, Compensation: above market base + bonus + equity Roles & Responsibilities Lead the design, development and scaling of an end to end data platform from ingestion to insights, ensuring that data is fast, reliable and ready for business use. Build and maintain scalable batch and streaming pipelines, transforming diverse data sources and third party application programming interfaces into trusted and low latency systems. Take full ownership of reliability, cost and service level objectives. This includes achieving ninety nine point nine percent uptime, maintaining minutes level latency and optimizing cost per terabyte. Conduct root cause analysis and provide long lasting solutions. Operate inference pipelines that enhance and enrich data. This includes enrichment, scoring and quality assurance using large language models and retrieval augmented generation. Manage version control, caching and evaluation loops. Work across teams to deliver data as a product through the creation of clear data contracts, ownership models, lifecycle processes and usage based decision making. Guide architectural decisions across the data lake and the entire pipeline stack. Document lineage, trade offs and reversibility while making practical decisions on whether to build internally or buy externally. Scale integration with application programming interfaces and internal services while ensuring data consistency, high data quality and support for both real time and batch oriented use cases. Mentor engineers, review code and raise the overall technical standard across teams. Promote data driven best practices throughout the organization. Qualifications Bachelors or Masters degree in Computer Science, Computer Engineering, Electrical Engineering, or Mathematics. Excellent written and verbal communication; proactive and collaborative mindset. Comfortable in hybrid or distributed environments with strong ownership and accountability. A founder-level bias for actionable to identify bottlenecks, automate workflows, and iterate rapidly based on measurable outcomes. Demonstrated ability to teach, mentor, and document technical decisions and schemas clearly. Core Experience 6 to 12 years of experience building and scaling production-grade data systems, with deep expertise in data architecture, modeling, and pipeline design. Expert SQL (query optimization on large datasets) and Python skills. Hands-on experience with distributed data technologies (Spark, Flink, Kafka) and modern orchestration tools (Airflow, Dagster, Prefect). Familiarity with dbt, DuckDB, and the modern data stack; experience with IaC, CI/CD, and observability. Exposure to Kubernetes and cloud infrastructure (AWS, GCP, or Azure). Bonus: Strong Node.js skills for faster onboarding and system integration. Previous experience at a high-growth startup (10 to 200 people) or early-stage environment with a strong product mindset.

Trexquant is a growing systematic fund at the forefront of quantitative finance, with a core team of highly accomplished researchers and engineers. To keep pace with our expanding global trading operations, we are seeking a C++ Market Data Engineer to design and build ultra-low-latency feed handlers for premier vendor feeds and major exchange multicast feeds. This is a high-impact role that sits at the heart of Trexquant's trading platform; the quality, speed, and reliability of your code directly influence every strategy we run. Responsibilities * Design & implement high-performance feed handlers in modern C++ for equities, futures, and options across global venues (e.g., NYSE, CME, Refinitiv RTS, Bloomberg B-PIPE). * Optimize for micro- and nanosecond latency using lock-free data structures, cache-friendly memory layouts, and kernel-bypass networking where appropriate. * Build reusable libraries for message decoding, normalization, and publication to internal buses shared by research, simulation, and live trading systems. * Collaborate with cross-functional teams to tune TCP/UDP multicast stacks, kernel parameters, and NIC settings for deterministic performance. * Provide robust failover, gap-recovery, and replay mechanisms to guarantee data integrity under packet loss or venue outages. * Instrument code paths with precision timestamping and performance metrics; drive continuous latency regression testing and capacity planning. * Partner closely with quantitative researchers to understand downstream data requirements and to fine-tune delivery formats for both simulation and live trading. * Produce clear architecture documents, operational run-books, and post-mortems; participate in a 24×7 follow-the-sun support rotation for mission-critical market-data services.

Bexorg is transforming drug discovery by restoring molecular activity in postmortem human brains. Our groundbreaking BrainEx platform enables direct experimentation on functionally preserved human brain tissue, generating massive, high-fidelity molecular datasets that power AI-driven drug discovery for CNS diseases. We are seeking a Data Engineer to help harness this unprecedented data. In this onsite, mid-level role, you will design and optimize the pipelines and cloud infrastructure that turn terabytes of raw experimental data into actionable insights, driving our mission to revolutionize treatments for central nervous system disorders. The Job: Data Ingestion & Pipeline Management: Manage and optimize massive data ingestion pipelines from cutting-edge experimental devices, ensuring reliable, real-time capture of complex molecular data. Cloud Data Architecture: Organize and structure large datasets in Google Cloud Platform, using tools like BigQuery and cloud storage to build a scalable data warehouse for fast querying and analysis of brain data. Large-Scale Data Processing: Design and implement robust ETL/ELT processes to handle PB scale data, emphasizing speed, scalability, and data integrity at each step of the process. Internal Data Services: Work closely with our software and analytics teams to expose processed data and insights to internal web applications. Build appropriate APIs or data access layers so that scientists and engineers can seamlessly visualize and interact with the data through our web platform. Internal Experiment Services: Work with our life science teams to ensure data entry protocols for seamless metadata integration and association with experimental data Infrastructure Innovation: Recommend and implement cloud infrastructure improvements (such as streaming technologies, distributed processing frameworks, and automation tools) that will future-proof our data pipeline. You will continually assess new technologies and best practices to increase throughput, reduce latency, and support our rapid growth in data volume. Qualifications and Skills: Experience with Google Cloud: Hands-on experience with Google Cloud services (especially BigQuery and related data tools) for managing and analyzing large datasets. You've designed or maintained data systems in a cloud environment and understand how to leverage GCP for big data workloads. Data Engineering Background: 3+ years of experience in data engineering or a similar role. Proven ability to build and maintain data pipelines dealing with petabyte-scale data. Proficiency in programming (e.g., Python, Java, or Scala) and SQL for developing data processing jobs and queries. Scalability & Performance Mindset: Familiarity with distributed systems or big data frameworks and a track record of optimizing data workflows for speed and scalability. You can architect solutions that handle exponential data growth without sacrificing performance. Biology Domain Insight: Exposure to biology or experience working with scientific data (e.g. genomics, bioinformatics, neuroscience) is a strong plus. While deep domain expertise isn't required, you should be excited to learn about our experimental data and comfortable discussing requirements with biologists. Problem-Solving & Collaboration: Excellent problem-solving skills, attention to detail, and a proactive attitude in tackling technical challenges. Ability to work closely with cross-functional teams (scientists, software engineers, data scientists) and communicate complex data systems in clear, approachable terms. Passion for the Mission: A strong desire to apply your skills to transform drug discovery. You are inspired by Bexorg's mission and eager to build the data backbone of a platform that could unlock new therapies for CNS diseases. Local to New Haven, CT preferred. No relocation offered for this position. Bexorg is an equal opportunity employer. We strive to create a supportive and inclusive workplace where contributions are valued and celebrated, and our employees thrive by being themselves and are inspired to do their best work. We seek applicants of all backgrounds and identities, across race, color, ethnicity, national origin or ancestry, citizenship, religion, sex, sexual orientation, gender identity or expression, veteran status, marital status, pregnancy or parental status, or disability. Applicants will not be discriminated against based on these or other protected categories or social identities. Bexorg will also consider for employment qualified applicants with criminal histories in a manner consistent with applicable federal, state and local law.

Trexquant is a growing systematic fund at the forefront of quantitative finance, with a core team of highly accomplished researchers and engineers. To keep pace with our expanding global trading operations, we are seeking a highly motivated and technically rigorous Data Platform Engineer to help modernize our foundational data infrastructure. As a Data Platform Engineer, you will be at the center of building the systems that ensure the quality, reliability, and discoverability of mission-critical data. Your work will directly impact the data operators and downstream consumers by creating robust tools, monitoring, and workflows that ensure accuracy, validity, and timeliness of data across the firm. Responsibilities * Architect and maintain core components of the Data Platform with a strong focus on reliability and scalability. * Build and maintain tools to manage data feeds, monitor validity, and ensure data timeliness. * Design and implement event-based data orchestration pipelines. * Evaluate and integrate data quality and observability tools via POCs and MVPs. * Stand up a data catalog system to improve data discoverability and lineage tracking. * Collaborate closely with infrastructure teams to support operational excellence and platform uptime. * Write and maintain data quality checks to validate real-time and batch data. * Validate incoming real-time data using custom Python-based validators. * Ensure low-level data correctness and integrity, especially in high-precision environments. * Build robust and extensible systems that will be used by data operators to ensure the health of our data ecosystem. * Own the foundational systems used by analysts and engineers alike to trust and explore our datasets.

Our Client A fast moving and venture backed advertising technology startup based in San Francisco. They have raised twelve million dollars in funding and are transforming how business to business marketers reach their ideal customers. Their identity resolution technology blends business and consumer signals to convert static audience lists into high match and cross channel segments without the use of cookies. By transforming first party and third party data into precision targetable audiences across platforms such as Meta, Google and YouTube, they enable marketing teams to reach higher match rates, reduce wasted advertising spend and accelerate pipeline growth. With a strong understanding of how business buyers behave in channels that have traditionally been focused on business to consumer activity, they are redefining how business brands scale demand generation and account based efforts. About Us Catalyst Labs is a leading talent agency with a specialized vertical in Applied AI, Machine Learning, and Data Science. We stand out as an agency thats deeply embedded in our clients recruitment operations. We collaborate directly with Founders, CTOs, and Heads of AI in those themes who are driving the next wave of applied intelligence from model optimization to productized AI workflows. We take pride in facilitating conversations that align with your technical expertise, creative problem-solving mindset, and long-term growth trajectory in the evolving world of intelligent systems. Location: San Francisco Work type: Full Time, Compensation: above market base + bonus + equity Roles & Responsibilities Lead the design, development and scaling of an end to end data platform from ingestion to insights, ensuring that data is fast, reliable and ready for business use. Build and maintain scalable batch and streaming pipelines, transforming diverse data sources and third party application programming interfaces into trusted and low latency systems. Take full ownership of reliability, cost and service level objectives. This includes achieving ninety nine point nine percent uptime, maintaining minutes level latency and optimizing cost per terabyte. Conduct root cause analysis and provide long lasting solutions. Operate inference pipelines that enhance and enrich data. This includes enrichment, scoring and quality assurance using large language models and retrieval augmented generation. Manage version control, caching and evaluation loops. Work across teams to deliver data as a product through the creation of clear data contracts, ownership models, lifecycle processes and usage based decision making. Guide architectural decisions across the data lake and the entire pipeline stack. Document lineage, trade offs and reversibility while making practical decisions on whether to build internally or buy externally. Scale integration with application programming interfaces and internal services while ensuring data consistency, high data quality and support for both real time and batch oriented use cases. Mentor engineers, review code and raise the overall technical standard across teams. Promote data driven best practices throughout the organization. Qualifications Bachelors or Masters degree in Computer Science, Computer Engineering, Electrical Engineering, or Mathematics. Excellent written and verbal communication; proactive and collaborative mindset. Comfortable in hybrid or distributed environments with strong ownership and accountability. A founder-level bias for actionable to identify bottlenecks, automate workflows, and iterate rapidly based on measurable outcomes. Demonstrated ability to teach, mentor, and document technical decisions and schemas clearly. Core Experience 6 to 12 years of experience building and scaling production-grade data systems, with deep expertise in data architecture, modeling, and pipeline design. Expert SQL (query optimization on large datasets) and Python skills. Hands-on experience with distributed data technologies (Spark, Flink, Kafka) and modern orchestration tools (Airflow, Dagster, Prefect). Familiarity with dbt, DuckDB, and the modern data stack; experience with IaC, CI/CD, and observability. Exposure to Kubernetes and cloud infrastructure (AWS, GCP, or Azure). Bonus: Strong Node.js skills for faster onboarding and system integration. Previous experience at a high-growth startup (10 to 200 people) or early-stage environment with a strong product mindset.