Data scientist jobs in Jersey City, NJ - 1,116 jobs

About Agentio Agentio enables marketers to buy creator led ads as easily and scalably as Meta or Google ads-automating sourcing, pricing, contracting, delivery, and measurement with AI-so work that took months now happens in minutes. We're on a mission to transform a $600B digital ad ecosystem by shifting digital ad spend into the hands of creators. That means better outcomes for marketers and enabling creators to live off their work-finally being paid in proportion to the value they create. That shift is accelerating: Unilever's CEO has said the company will move roughly half of its ad budget into social and creators-Unilever is among the world's largest advertisers, spending around $9-10B annually. As these dollars move, they need performance-grade pipes; Agentio is how those dollars flow to creators with the speed, control, and measurement marketers expect. We enable brands like Uber, DoorDash, and Bombas to run creator campaigns with the same rigor, control, and accountability as their core performance channels. Agentio's investors include Benchmark, Craft, and AlleyCorp. Agentio has been named to Forbes' list of Next Billion Dollar Startups, 2025. We've raised $16M to date, our product is already used and loved by the world's leading marketers and creators- and we're just getting started. Data is Our Growth Engine Our platform routes budgets to the right creators, at the right price, with clear attribution. We ingest rich first-party signals across creative briefs, audiences, content, and outcomes; link them to conversions; and train LLM-driven ranking and pricing models that guide every step-from discovery and acceptance likelihood to pacing and scale. Each campaign feeds back new data, creating a compounding learning loop that makes matching, forecasting, and measurement more efficient with every use. We're expanding our data practice and hiring foundational teammates. Whether you analyze behavior, model outcomes, run experiments, or build robust data and ML tooling, you'll have an immediate impact-shaping product decisions, improving measurement, and delivering the pipelines and services that power the platform. At Agentio, data drives decisions-what we build, how we price, and where we scale-so creators and brands win together. If you're curious, collaborative, and excited to own outcomes in a fast-moving environment, let's talk. You Nimble, hungry, humble, and adaptive to change Excited to learn and grow in a fast-paced environment Proven track record of applying analytical/statistical methods to tackle real-world problems using big data. A true problem-solver and self-starter, with incredible ambition and drive Competitive and highly motivated to exceed expectations Ready to roll up your sleeves, get things done, and work harder than you've likely ever worked before - with far greater reward A positive, honest, empathetic, and curious teammate What You'll Get The opportunity to build a first-of-its kind business as an early team-member and make a meaningful impact in the way brands share their stories and creators live off their work. Crash-course in what it takes to scale a start-up with first-hand exposure to the different foundational business drivers and needs. The chance to work with an exceptional team and help build our engineering culture A collaborative, transparent, and engaging work environment. Benefits & Perks Flexible PTO - Take the time you need to recharge Comprehensive Health Coverage - Top medical plan through Aetna Dental & Vision Plans - Protect your smile and your sight with coverage from Guardian 401(k) Retirement Plan - Invest in your future while you build your career $100 Monthly Lifestyle Credit - Use it to shop with our amazing Agentio Brand Partners Free Lunch 3x a week! - We order lunch as a team on Mondays, Wednesdays, and Fridays Gym in the building! - Your workout, right downstairs The estimated base compensation for this role is between $130,000 & $ 225,000. Individual compensation is determined by skills, qualifications, and experience. In addition, this role is eligible for equity and competitive benefits. #J-18808-Ljbffr

EDO is the TV outcomes company - a leading platform measuring Convergent TV advertising. Combining real-time engagement signals with world-class decision science, EDO maximizes creative and media performance for modern marketers at leading brands, TV networks, entertainment studios, and ad agencies. EDO's investment-grade data align advertising investments to business results - with detailed competitive, category, historical, and predictive intelligence. EDO is headquartered in Los Angeles and New York City. We also have an office space in San Francisco. We recognize the benefits of hybrid working and want to create the best balance to ensure we can continue working together effectively. For this role, we have a hybrid work policy of 2 days a week in any EDO office. The Role Data Scientists at EDO drive EDO's modeling and analytical methodology to measure the effect that television and streaming ads have on consumer behaviors, primarily consumers' online search and website visits. What You Will Do Enhance EDO's AdEngage platform that measures the effectiveness of linear and streaming TV ads, and enable it to process new types of data and serve new client needs. Test out new methods for modeling ad effectiveness on trillion-event data sets spanning millions of households for several years. Develop reusable tools and building blocks for connecting data sets. Build, diagnose, and tune models, then automate the modeling and diagnostics. Work on a small team and take ownership of high impact projects. What We Are Looking For 3+ years professional experience doing hands-on analysis and writing clean, reusable code in Python. Interpersonal and communication skills to work effectively on a distributed team. Experience building and tuning XGBoost (or similar GBM) models, and with cross-validation techniques, and familiarity with a handful of other modeling tools. Experience with git and exposure to unit testing concepts. Understanding of biased data and adjustment methods including weighting and resampling. Proficiency with analytic queries in SQL and relational databases (we primarily use Snowflake), with experience interfacing directly with databases from Python (we leverage SQLAlchemy Core heavily). Building models of sales lift, running controlled experiments, modeling marketing effectiveness. Familiarity with panel datasets, especially ones with missing data and attrition. Development and test pipelines, continuous integration. Development of feature engineering pipelines and DBT. Implementing or auditing policy compliance in data pipelines and workflows. EDO offers engineering teams a full suite of GenAI tools to assist in developing their work, and resources to best enable use of these tools, as desired. EDO offers a competitive compensation package. Components of compensation include: Mid-stage equity and competitive salary Flexible Time Off Medical, dental and vision coverage, deeply discounted by EDO 401(k) plan, FSA, HSA When in an office, employee meals, snacks, and more fully paid for The base salary range for this position is $120,000 to $150,000, PLUS equity in a mid-stage company. Compensation will be determined based on the skills, qualifications, experience, location and the level of education attained of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time. EDO is an equal opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any legally protected status. All your information will be kept confidential according to EEO guidelines. #J-18808-Ljbffr

Founded by Arun Gupta (former CEO of Grailed, which sold to GOAT Group in 2022) and Bob Whitney (Anthropic, NYT Games), we're on a mission to create safe, hands‑on AI experiences that fuel kids' imaginations rather than replace them. Our first product, Stickerbox, is the world's first voice‑to‑sticker printer. A device that instantly transforms a child's spoken ideas into printable, colorable stickers. We sold out our first run shipping for the holidays, and it's already being called "one of the first products to make AI feel magical for kids and grounded for parents." We have a $7M funding round led by Maveron (backers of Lovevery), Serena Ventures, and Ai2 (The Allen Institute). Stickerbox is bringing imagination to life for kids nationwide! Why are we hiring? The technical challenge is real. We're running real‑time audio transcription, proprietary content safety systems, and custom image generation, all serving thousands of concurrent users with sub‑second latency. We're training our own models from scratch, optimizing for kid‑friendly aesthetics, and building safety guardrails that actually work. We need a Data Scientist to own data quality, evaluation, and ML optimization across this entire pipeline. You'll work with the team to define what to train on, how to measure success, and how to make our models better every day. What you'll do As our first Data Science hire, you'll collaborate with us on: Model Training & Data Build and curate large‑scale image datasets for training custom models Design annotation pipelines and data quality processes Analyze training runs and model outputs to guide iteration Work with our team to define what to train on and how to evaluate it ML Pipeline Optimization Optimize our transcription pipeline for accuracy and latency Improve image generation quality, prompt adherence, and consistency Identify bottlenecks and failure modes across the pipeline Run experiments and A/B tests to measure improvements Safety & Content Moderation Refine content safety systems for child‑appropriate outputs, and develop new ones Build on our evaluation datasets for safety edge cases Analyze moderation performance and reduce false positives/negatives Stay current on best practices for AI safety in generative systems Evaluation & Metrics Build evaluation frameworks to measure model performance at scale Define metrics that correlate with user satisfaction (aesthetic quality, relevance, safety) Develop automated evaluation pipelines (LLM‑as‑judge, CLIP scores, human eval) Track experiments and communicate findings to the team Prompt Engineering Optimize prompts for transcription accuracy and image generation quality Develop systematic approaches to prompt testing and iteration Build prompt templates and guidelines for different use cases What we're looking for 5+ years in data science or applied ML Experience optimizing production ML systems Strong statistical and analytical skills Familiarity with LLMs and image generation models Python proficiency; comfortable with PyTorch Experience building evaluation frameworks Track record of improving ML system performance through data and experimentation Nice to have Experience with content moderation or trust & safety Background in speech/audio ML or computer vision Experience with human annotation pipelines (Label Studio, Scale AI) Familiarity with prompt engineering techniques and LLM‑based evaluation Location: NYC only, On‑site (flexible on WFH but we like to be in office the majority of the week) in our Brooklyn based office, close to most major train lines. Salary Range: $150k - $250k base + equity and benefits #J-18808-Ljbffr

A global marketplace for creative goods is seeking a Data Engineer to join their Core Data team. This role involves building and maintaining data pipelines, ensuring data quality, and collaborating with product engineering teams to analyze buyer behavior. The ideal candidate has experience with streaming data processing and SQL, though enthusiasm and a willingness to learn are equally valued. This full-time position offers competitive salary and benefits, as well as opportunities for equity and bonuses. #J-18808-Ljbffr

A leading tech company based in New York is seeking an experienced Senior Data Scientist to develop recommendation models and assist customers in utilizing the Shaped Platform. The ideal candidate will have proficiency in ML, Python, and SQL, with at least 3 years of industry experience. This role involves collaborating with a diverse customer base to solve ranking challenges and contribute to product roadmaps. Join us to innovate the future of AI! #J-18808-Ljbffr

Job Title: Analyst, Data Scientist Salary: $70,000-$90,000 Contact: ******************************** is not available for C2C or C2H and the client is unable to sponsor at this time. About the Company We are partnering with a leading organization in the textiles and apparel sector, known for its commitment to innovation, quality, and operational excellence within the retail industry. The company is focused on enhancing business processes and delivering exceptional value to its customers through data-driven decision-making. Role Overview The Analyst, Data Scientist plays a critical role in developing and maintaining reporting tools, including metrics, dashboards, and analytical platforms. This position supports strategic and operational decision-making by applying data analysis to identify insights, maintain process controls, and drive continuous improvement across the organization. Key Responsibilities Manage reporting requests from field operations by defining technical requirements and developing reports, metrics, and dashboards using SQL and Power BI Design and build advanced Power BI dashboards leveraging DAX, Power Query, and other advanced features Perform data cleaning and analysis, translating complex analytical results into clear, actionable insights Collaborate with business stakeholders and IT teams to align on project objectives and deliverables Support strategic initiative planning through prioritization, estimation, and analysis Gather, document, and maintain detailed business and technical requirements Participate in problem-solving sessions with business users and leadership to address analytical challenges Lead change management efforts and deliver training to end users as needed Serve as a liaison between business teams and IT to resolve system issues and improve processes Provide regular project updates and communicate issue resolution status to stakeholders Qualifications Bachelor's degree in Engineering, Mathematics, Computer Science, or a related field 1-2 years of experience developing business or technology solutions Strong proficiency in Power BI, including DAX and Power Query Solid understanding of data warehousing and business intelligence concepts Ability to read and write SQL Familiarity with R, Python, and machine learning concepts (theoretical or practical) is a plus Advanced skills in Microsoft Office tools, including Excel, PowerPoint, Word, Visio, and SharePoint Experience in a corporate retail environment is preferred This role is ideal for a proactive, analytical professional who thrives in a fast-paced environment. The successful candidate will demonstrate strong communication and collaboration skills and the ability to work effectively across cross-functional teams.

Pricing Reinsurance Actuary New York, USA Our Client Our client is a modern reinsurance company specializing in data-driven portfolios of Property & Casualty (P&C) risk. The firm's approach combines deep industry relationships, a sustainable capital structure, and a partner-first philosophy to deliver efficient and innovative reinsurance solutions. As the company continues to grow, Northern is seeking a Pricing Actuary to strengthen its technical and analytical capabilities within the underwriting team. This is a unique opportunity to join a collaborative and forward-thinking environment that values expertise, precision, and long-term partnerships. Responsibilities Lead the pricing of reinsurance treaties, with a primary focus on U.S. Casualty Programs, and expand to other lines as the portfolio grows. Provide core input into transactional and portfolio-level underwriting decisions. Conduct peer reviews of pricing models and assumptions prepared by other team members. Support quarterly loss ratio analyses to monitor portfolio performance, identify trends, and inform capital management strategies. Contribute to the annual reserve study process and present insights to the executive leadership team. Execute benchmark parameter studies and communicate findings to management to support strategic planning. Participate in broker meetings and client visits, helping to structure and negotiate optimal treaty terms. Enhance portfolio monitoring and efficiency through process improvement, automation, and the development of analytical tools and dashboards. Some travel may be required. Qualifications Degree in Actuarial Science, Mathematics, Statistics, or a related field. FCAS or ACAS designation (or international equivalent) strongly preferred. Minimum of 8-10 years of actuarial experience in Property & Casualty reinsurance or insurance pricing. Proven expertise in casualty and specialty lines, including professional liability, D&O, and E&O. Strong analytical and problem-solving skills, with demonstrated experience in data modeling, pricing tools, and portfolio analytics. Excellent communication and collaboration abilities, capable of working closely with underwriting, finance, and executive teams. The Ideal Profile A technically strong, business-minded actuary who thrives in a dynamic, collaborative, and data-driven environment. Recognized for analytical rigor, attention to detail, and the ability to translate complex models into actionable insights. Values teamwork, intellectual curiosity, and innovation in solving industry challenges. Seeks to contribute meaningfully to a growing, entrepreneurial organization shaping the future of reinsurance. Why Join the Team This is a rare opportunity to join a modern, high-growth reinsurer where your analytical insight and strategic thinking will directly influence underwriting decisions and company performance. Northern offers a collaborative culture, flexible hybrid work model, and the chance to shape cutting-edge reinsurance strategies in partnership with leading underwriters and actuaries. REF# WEB1429

Our client is a $28B NY based multi-strategy Hedge Fund currently seeking to add a talented Associate to their Data & Performance Analytics Team. This individual will be working closely with senior managers across finance, investment management, operations, technology, investor services, compliance/legal, and marketing. Responsibilities This role will be responsible for Compiling periodical fund performance analyses Review and analyze portfolio performance data, benchmark performance and risk statistics Review and make necessary adjustments to client quarterly reports to ensure reports are sent out in a timely manner Work with all levels of team members across the organization to help coordinate data feeds for various internal and external databases, in effort to ensure the integrity and consistency of portfolio data reported across client reporting systems Apply queries, pivot tables, filters and other tools to analyze data. Maintain client relationship management database and providing reports to Directors on a regular basis Coordinate submissions of RFPs by working with RFP/Marketing Team and other groups internally to gather information for accurate data and performance analysis Identifying opportunities to enhance the strategic reporting platform by gathering and analyzing field feedback and collaborating with partners across the organization Provide various ad hoc data research and analysis as needed. Desired Skills and Experience Bachelor's Degree with at least 2+ years of Financial Services/Private Equity data/client reporting experience Proficiency in Microsoft Office, particularly Excel Modeling Technical knowledge, data analytics using CRMs (Salesforce), Excel, PowerPoint Outstanding communication skills, proven ability to effectively work with all levels of Managment Comfortable working in a fast-paced, dead-line driven dynamic environment Innovative and creative thinker Must be detail oriented

Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do's, such as furniture assembly, handyman work, moving help, and much more. At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We're looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we're creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world. Taskrabbit is a remote-first company with employees distributed across the US and EU 5-time Best Places to Work in 2022 by BuiltIn. Including Best Companies in SF, Best Mid-Sized Companies, and Best Benefits DataBird journal's “Best Places” Best Companies for Diversity, #1 2019 and 2020 DataBird journal's “Best Places” Best Companies for Women, #4 2019 and #1 2020 Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed!. About the Role We are seeking a Staff Data Engineer to lead the design, development, and optimization of our data infrastructure and analytics layers, enabling the creation of reliable, scalable, and high-quality data products across the company. This role will report to the Director of Data Engineering and Applications and work closely with both technical teams and non-technical stakeholders across the business. While this is an individual contributor role, it emphasizes mentorship and strategic guidance across both data engineering and analytics engineering functions. The ideal candidate has deep experience building and maintaining modern data platforms using tools such as dbt, Airflow, and Snowflake (or equivalent), and brings strong expertise in data modeling, orchestration, and production-grade data pipelines. They excel at engaging with non-technical stakeholders to understand business needs and are skilled at translating those needs into well-defined metrics, semantic models, and self-serve analytical tools. They are comfortable shaping architectural direction, promoting best practices across the team, and thrive in environments that require cross-functional collaboration, clear communication, and a strong sense of ownership. What You'll Work On: Design, build, and maintain scalable, reliable data pipelines and infrastructure to support analytics, operations, and product use cases Develop and evolve dbt models, semantic layers, and data marts that enable trustworthy, self-serve analytics across the business Collaborate with non-technical stakeholders to deeply understand their business needs and translate them into well-defined metrics and analytical tools Lead architectural decisions for our data platform, ensuring it is performant, maintainable, and aligned with future growth Build and maintain data orchestration and transformation workflows using tools like Airflow, dbt, and Snowflake (or equivalent) Champion data quality, documentation, and observability to ensure high trust in data across the organization Mentor and guide other engineers and analysts, promoting best practices in both data engineering and analytics engineering disciplines Your Areas Of Expertise: Expertise in building and maintaining ELT data pipelines using modern tools such as dbt, Airflow, and Fivetran Deep experience with cloud data warehouses such as Snowflake, BigQuery, or Redshift Strong data modeling skills (e.g., dimensional modeling, star/snowflake schemas) to support both operational and analytical workloads Proficient in SQL and at least one general-purpose programming language (e.g., Python, Java, or Scala) Experience with streaming data platforms (e.g., Kafka, Kinesis, or equivalent) and real-time data processing patterns Familiarity with infrastructure-as-code tools like Terraform and DevOps practices for managing data platform components Hands-on experience with BI and semantic layer tools such as Looker, Mode, Tableau, or equivalent At Taskrabbit, our approach to compensation is designed to be competitive, transparent, and equitable. total compensation consists of base pay + bonus + benefits + perks. The base pay range for this position is $136,000 - $180,000. This range is representative of base pay only, and does not include any other total cash compensation amounts, such as company bonus or benefits. Final offer amounts may vary from the amounts listed above and will be determined by factors including, but not limited to, relevant experience, qualifications, geography, and level. You'll love working here because: Taskrabbit is a Remote-First Company. We value flexibility and choice but also stay committed to regular in-person connection. The People. You will be surrounded by some of the most talented, supportive, smart, and kind leaders and teams -- people you can be proud to work with! The Diverse Culture. We believe that we make better decisions when our workforce reflects the diversity of the communities in which we operate. Women make up half of our leadership team and our diversity representation is above that of the tech industry average. The Perks. Taskrabbit offers our employees with employer-paid health insurance and a 401k match with immediate vesting for our US based employees. We offer all of our global employees generous and flexible time off with 2 company-wide closure weeks, Taskrabbit product stipends, wellness + productivity + education stipends, IKEA discounts, reproductive health support, and more. Benefits vary by country of employment. Taskrabbit's commitment to Diversity and Inclusion: An Active Commitment to Equity within our Company and Platform. We are an inclusive community where all who share our mission and values belong. Our anti-racist culture actively strengthens the knowledge, understanding, and awareness of underrepresented experiences and our ongoing allyship commitment. Our diverse team represents the communities we serve, breaking down systemic barriers, and transforming lives- one action at a time. Taskrabbit is an equal opportunity employer and values diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, ancestry, citizenship, sex, gender, gender identity, sexual orientation, age, marital status, military/veteran status, or disability status. Taskrabbit is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Taskrabbit will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. Taskrabbit will never use text or chat applications to conduct interviews. We have a thoughtful and interactive interview process that includes an initial recruiter phone screen and several video-based interviews with our hiring teams. Communications will always be conducted by taskrabbit.com domain names. Create a Job Alert Interested in building your career at Taskrabbit? Get future opportunities sent straight to your email. 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As set forth in Taskrabbit's Equal Employment Opportunity policy,we do not discriminate on the basis of any protected group status under any applicable law. If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection.As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measurethe effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categoriesis as follows: A "disabled veteran" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service-connected disability. 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Disabilities include, but are not limited to: Alcohol or other substance use disorder (not currently using drugs illegally) Autoimmune disorder, for example, lupus, fibromyalgia, rheumatoid arthritis, HIV/AIDS Blind or low vision Cancer (past or present) Cardiovascular or heart disease Celiac disease Cerebral palsy Deaf or serious difficulty hearing Diabetes Disfigurement, for example, disfigurement caused by burns, wounds, accidents, or congenital disorders Epilepsy or other seizure disorder Gastrointestinal disorders, for example, Crohn's Disease, irritable bowel syndrome Intellectual or developmental disability Mental health conditions, for example, depression, bipolar disorder, anxiety disorder, schizophrenia, PTSD Missing limbs or partially missing limbs Mobility impairment, benefiting from the use of a wheelchair, scooter, walker, leg brace(s) and/or other supports Nervous system condition, for example, migraine headaches, Parkinson's disease, multiple sclerosis (MS) Neurodivergence, for example, attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, dyslexia, dyspraxia, other learning disabilities Partial or complete paralysis (any cause) Pulmonary or respiratory conditions, for example, tuberculosis, asthma, emphysema Short stature (dwarfism) Traumatic brain injury Disability Status Select... 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A leading crypto and Web3 platform in San Francisco is seeking a Staff Data Platform Engineer to own and evolve the data warehouse infrastructure. This role requires a minimum of 8 years of experience in data engineering and strong hands-on experience with Databricks and AWS. The ideal candidate will also mentor engineers and influence architectural decisions. The position offers a competitive salary, flexible work options, and comprehensive benefits. #J-18808-Ljbffr

About Beauty by Imagination: Beauty by Imagination is a global haircare company dedicated to boosting self-confidence with imaginative solutions for every hair moment. We are a platform company of diverse, market-leading brands, including Wet Brush, Goody, Bio Ionic, and Ouidad - all of which are driven to be the most trusted choice for happy, healthy hair. Our talented team is passionate about delivering high-performing products for consumers and salon professionals alike. Position Overview: We are looking for a skilled Data Engineer to design, build, and maintain our enterprise Data Warehouse (DWH) and analytics ecosystem - with a growing focus on enabling AI-driven insights, automation, and enterprise-grade AI usage. In this role, you will architect scalable pipelines, improve data quality and reliability, and help lay the foundational data structures that power tools like Microsoft Copilot, Copilot for Power BI, and AI-assisted analytics across the business. You'll collaborate with business stakeholders, analysts, and IT teams to modernize our data environment, integrate complex data sources, and support advanced analytics initiatives. Your work will directly influence decision-making, enterprise reporting, and next-generation AI capabilities built on top of our Data Warehouse. Key Responsibilities Design, develop, and maintain Data Warehouse architecture, including ETL/ELT pipelines, staging layers, and data marts. Build and manage ETL workflows using SQL Server Integration Services (SSIS) and other data integration tools. Integrate and transform data from multiple systems, including ERP platforms such as NetSuite. Develop and optimize SQL scripts, stored procedures, and data transformations for performance and scalability. Support and enhance Power BI dashboards and other BI/reporting systems. Implement data quality checks, automation, and process monitoring. Collaborate with business and analytics teams to translate requirements into scalable data solutions. Contribute to data governance, standardization, and documentation practices. Support emerging AI initiatives by ensuring model-ready data quality, accessibility, and semantic alignment with Copilot and other AI tools. Required Qualifications Proven experience with Data Warehouse design and development (ETL/ELT, star schema, SCD, staging, data marts). Hands-on experience with SSIS (SQL Server Integration Services) for building and managing ETL workflows. Strong SQL skills and experience with Microsoft SQL Server. Proficiency in Power BI or other BI tools (Tableau, Looker, Qlik). Understanding of data modeling, performance optimization, and relational database design. Familiarity with Python, Airflow, or Azure Data Factory for data orchestration and automation. Excellent analytical and communication skills. Preferred Qualifications Experience with cloud data platforms (Azure, AWS, or GCP). Understanding of data security, governance, and compliance (GDPR, SOC2). Experience with API integrations and real-time data ingestion. Background in finance, supply chain, or e-commerce analytics. Experience with NetSuite ERP or other ERP systems (SAP, Oracle, Dynamics, etc.). AI Focused Preferred Skills: Experience implementing AI-driven analytics or automation inside Data Warehouses. Hands-on experience using Microsoft Copilot, Copilot for Power BI, or Copilot Studio to accelerate SQL, DAX, data modeling, documentation, or insights. Familiarity with building RAG (Retrieval-Augmented Generation) or AI-assisted query patterns using SQL Server, Synapse, or Azure SQL. Understanding of how LLMs interact with enterprise data, including grounding, semantic models, and data security considerations (Purview, RBAC). Experience using AI tools to optimize ETL/ELT workflows, generate SQL scripts, or streamline data mapping/design. Exposure to AI-driven data quality monitoring, anomaly detection, or pipeline validation tools. Experience with Microsoft Fabric, semantic models, or ML-integrated analytics environments. Soft Skills Strong analytical and problem-solving mindset. Ability to communicate complex technical concepts to business stakeholders. Detail-oriented, organized, and self-motivated. Collaborative team player with a growth mindset. Impact You will play a key role in shaping the company's modern data infrastructure - building scalable pipelines, enabling advanced analytics, and empowering the organization to safely and effectively adopt AI-powered insights across all business functions. Our Tech Stack SQL Server, SSIS, Azure Synapse Python, Airflow, Azure Data Factory Power BI, NetSuite ERP, REST APIs CI/CD (Azure DevOps, GitHub) What We Offer Location: New York, NY (Hybrid work model) Employment Type: Full-time Compensation: Competitive salary based on experience Benefits: Health insurance, 401(k), paid time off Opportunities for professional growth and participation in enterprise AI modernization initiatives

Your work will change lives. Including your own. 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 Team OpenAI's User Operations organization is building the data and intelligence layer behind AI-assisted operations - the systems that decide when automation should help users, when humans should step in, and how both improve over time. Our flagship platform is transforming customer support into a model for “agent-first” operations across OpenAI. About the Role As a Data Scientist on User Operations, you'll design the models, metrics, and experimentation frameworks that power OpenAI's human-AI collaboration loop. You'll build systems that measure quality, optimize automation, and turn operational data into insights that improve product and user experience at scale. You'll partner closely with Support Automation Engineering, Product, and Data Engineering to ensure our data systems are production-grade, trusted, and impactful. This role is based in San Francisco or New York City. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. Why it matters Every conversation users have with OpenAI products produces signals about how humans and AI interact. User Ops Data Science turns those signals into insights that shape how we support users today and design agentic systems for tomorrow. This is a unique opportunity to help define how AI collaboration at scale is measured and improved inside OpenAI. In this role, you will: Build and own metrics, classifiers, and data pipelines that determine automation eligibility, effectiveness, and guardrails. Design and evaluate experiments that quantify the impact of automation and AI systems on user outcomes like resolution quality and satisfaction. Develop predictive and statistical models that improve how OpenAI's support systems automate, measure, and learn from user interactions. Partner with engineering and product teams to create feedback loops that continuously improve our AI agents and knowledge systems. Translate complex data into clear, actionable insights for leadership and cross-functional stakeholders. Develop and socialize dashboards, applications, and other ways of enabling the team and company to answer product data questions in a self-serve way Contribute to establishing data science standards and best practices in an AI-native operations environment. Partner with other data scientists across the company to share knowledge and continually synthesize learnings across the organization You might thrive in this role if you have: 10+ years of experience in data science roles within product or technology organizations. Expertise in statistics and causal inference, applied in both experimentation and observational causal inference studies. Expert-level SQL and proficiency in Python for analytics, modeling, and experimentation. Proven experience designing and interpreting experiments and making statistically sound recommendations. Experience building data systems or pipelines that power production workflows or ML-based decisioning. Experience developing and extracting insights from business intelligence tools, such as Mode, Tableau, and Looker. Strategic and impact-driven mindset, capable of translating complex business problems into actionable frameworks. Ability to build relationships with diverse stakeholders and cultivate strong partnerships. Strong communication skills, including the ability to bridge technical and non-technical stakeholders and collaborate across various functions to ensure business impact. Ability to operate effectively in a fast-moving, ambiguous environment with limited structure. Strong communication skills and the ability to translate complex data into stories for non-technical partners. Nice-to-haves: Familiarity with large language models or AI-assisted operations platforms. Experience in operational automation or customer support analytics. Background in experimentation infrastructure or human-AI interaction systems. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI's Affirmative Action and Equal Employment Opportunity Policy Statement. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link. OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

About Gap Inc. Our brands bridge the gaps we see in the world. Old Navy democratizes style to ensure everyone has access to quality fashion at every price point. Athleta unleashes the potential of every woman, regardless of body size, age or ethnicity. Banana Republic believes in sustainable luxury for all. And Gap inspires the world to bring individuality to modern, responsibly made essentials. This simple idea-that we all deserve to belong, and on our own terms-is core to who we are as a company and how we make decisions. Our team is made up of thousands of people across the globe who take risks, think big, and do good for our customers, communities, and the planet. Ready to learn fast, create with audacity and lead boldly? Join our team. About the Role Gap Inc. is seeking a Principal Data Scientist with deep expertise in operations research and machine learning to lead the design and deployment of advanced analytics solutions across the Product-to-Market (P2M) space. This role focuses on driving enterprise-scale impact through optimization and data science initiatives spanning pricing, inventory, and assortment optimization. The Principal Data Scientist serves as a senior technical and strategic thought partner, defining solution architectures, influencing product and business decisions, and ensuring that analytical solutions are both technically rigorous and operationally viable. The ideal candidate can lead end-to-end solutioning independently, manage ambiguity and complex stakeholder dynamics, and communicate technical and business risk effectively across teams and leadership levels. What You'll Do * Lead the framing, design, and delivery of advanced optimization and machine learning solutions for high-impact retail supply chain challenges. * Partner with product, engineering, and business leaders to define analytics roadmaps, influence strategic priorities, and align technical investments with business goals. * Provide technical leadership to other data scientists through mentorship, design reviews, and shared best practices in solution design and production deployment. * Evaluate and communicate solution risks proactively, grounding recommendations in realistic assessments of data, system readiness, and operational feasibility. * Evaluate, quantify, and communicate the business impact of deployed solutions using statistical and causal inference methods, ensuring benefit realization is measured rigorously and credibly. * Serve as a trusted advisor by effectively managing stakeholder expectations, influencing decision-making, and translating analytical outcomes into actionable business insights. * Drive cross-functional collaboration by working closely with engineering, product management, and business partners to ensure model deployment and adoption success. * Quantify business benefits from deployed solutions using rigorous statistical and causal inference methods, ensuring that model outcomes translate into measurable value * Design and implement robust, scalable solutions using Python, SQL, and PySpark on enterprise data platforms such as Databricks and GCP. * Contribute to the development of enterprise standards for reproducible research, model governance, and analytics quality. Who You Are * Master's or Ph.D. in Operations Research, Operations Management, Industrial Engineering, Applied Mathematics, or a closely related quantitative discipline. * 10+ years of experience developing, deploying, and scaling optimization and data science solutions in retail, supply chain, or similar complex domains. * Proven track record of delivering production-grade analytical solutions that have influenced business strategy and delivered measurable outcomes. * Strong expertise in operations research methods, including linear, nonlinear, and mixed-integer programming, stochastic modeling, and simulation. * Deep technical proficiency in Python, SQL, and PySpark, with experience in optimization and ML libraries such as Pyomo, Gurobi, OR-Tools, scikit-learn, and MLlib. * Hands-on experience with enterprise platforms such as Databricks and cloud environments * Demonstrated ability to assess, communicate, and mitigate risk across analytical, technical, and business dimensions. * Excellent communication and storytelling skills, with a proven ability to convey complex analytical concepts to technical and non-technical audiences. * Strong collaboration and influence skills, with experience leading cross-functional teams in matrixed organizations. * Experience managing code quality, CI/CD pipelines, and GitHub-based workflows. Preferred Qualifications * Experience shaping and executing multi-year analytics strategies in retail or supply chain domains. * Proven ability to balance long-term innovation with short-term deliverables. * Background in agile product development and stakeholder alignment for enterprise-scale initiatives. Benefits at Gap Inc. * Merchandise discount for our brands: 50% off regular-priced merchandise at Old Navy, Gap, Banana Republic and Athleta, and 30% off at Outlet for all employees. * One of the most competitive Paid Time Off plans in the industry.* * Employees can take up to five "on the clock" hours each month to volunteer at a charity of their choice.* * Extensive 401(k) plan with company matching for contributions up to four percent of an employee's base pay.* * Employee stock purchase plan.* * Medical, dental, vision and life insurance.* * See more of the benefits we offer. * For eligible employees Gap Inc. is an equal-opportunity employer and is committed to providing a workplace free from harassment and discrimination. We are committed to recruiting, hiring, training and promoting qualified people of all backgrounds, and make all employment decisions without regard to any protected status. We have received numerous awards for our long-held commitment to equality and will continue to foster a diverse and inclusive environment of belonging. In 2022, we were recognized by Forbes as one of the World's Best Employers and one of the Best Employers for Diversity. Salary Range: $201,700 - $267,300 USD Employee pay will vary based on factors such as qualifications, experience, skill level, competencies and work location. We will meet minimum wage or minimum of the pay range (whichever is higher) based on city, county and state requirements.

Job DescriptionJob Title: Data Scientist Job Type: Full-Time We are seeking a Data Scientist to lead the design, training, and deployment of production-grade computer vision models. This role owns the full ML lifecycle from data strategy and experimentation to deployable models-while collaborating closely with a distributed ML team in a fast-paced startup environment. Key Responsibilities Design, train, and evaluate computer vision models for real-world use cases such as detection, tracking, and activity understanding. Own the end-to-end data lifecycle, including defining data requirements, guiding collection, improving labeling quality, and driving continuous dataset improvement. Build and maintain training pipelines and experimentation frameworks, including preprocessing, augmentation, and evaluation tooling. Contribute production-quality code and collaborate with ML and backend engineers to deliver deployable model artifacts and interfaces. Review and mentor other ML contributors, providing feedback on modeling decisions, experimentation rigor, and implementation quality. Partner with technical leadership to define research roadmaps, modeling strategies, and rollout plans. Prototype and evaluate new architectures, loss functions, and training strategies, transitioning successful approaches into production. Define performance metrics, validation processes, and monitoring strategies to ensure robustness in real-world environments. Operate effectively in a startup setting, rapidly iterating based on product needs and experimental results. & Requirements: 3+ years in computer vision or applied machine learning Strong experience with PyTorch/TensorFlow and modern CV architectures End-to-end ownership of datasets and training pipelines Production-oriented engineering mindset and mentoring ability

Bachelors or Master's degree with specialization in Computer Science, Information Systems, Mathematics, Statistics or other quantitative disciplines Excellent ability to query large datasets using SQL queries and working with databases Excellent in programming languages such as Java, Python, etc. Experience in data extraction and processing, using MapReduce, Pig, Hive, etc. Proficient programming skills using SAS and/or R Knowledge of building and applying machine learning or predictive modeling Strong problem solving skills Exceptional ability to communicate and present findings clearly to both technical and non-technical audiences Excellent interpersonal and collaboration skills Additional Information Thanks & Regards, Praveen K. Paila ************

Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes. More than 500,000 organizations, including 80% of the Fortune 100, rely on Airtable to transform how work gets done. Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes. More than 500,000 organizations, including 80% of the Fortune 100, rely on Airtable to transform how work gets done. Our data team's mission is to fuel Airtable's growth and operations. We are a strategic enabler, by building high-quality and customer-centric data products and solutions. We are looking for a Data Scientist to work directly with Airtable's business stakeholders. Your data product will be instrumental in accelerating the efficiency of Customer Engagement (CE) organizations including sales, CSG and revenue operations teams. This role offers the opportunity to significantly impact Airtable's strategy and go-to-market execution, providing you with a platform to deploy your data skills in a way that directly contributes to our company's growth and success. What you'll do Champion AI Driven Data Product with Scalability: Design and implement ML models and AI solutions to enable CE team with actionable insights and recommendations. Build scalable data pipelines and automated workflows with MLOps best practices. Support Key Business Processes: Provide strategic insights, repeatable frameworks and thought partnership independently to support key CE business processes like territory carving, annual planning, pricing optimization and performance attribution, etc.. Strategic Analysis: Drive in-depth deep-dive analysis to ensure accuracy and relevance. Influence the business stakeholders with a good story telling of the data. Tackle ambiguous problems to uncover business value with minimal oversight. Develop Executive Dashboards: Design, build, and maintain high-quality dashboards and BI tools. Partner with Revenue Operations team to enable vast roles of CE team efficiently with the data products. Strong Communication Skills: Effectively communicate the “so-what” of an analysis, illustrating how insights can be leveraged to drive business impact across the organization. Who you are Education: Bachelor degree in a quantitative discipline (Math, Statistics, Operations Research, Economics, Engineering, or CS), MS/MBA preferred. Industry Experience: 4+ years of working experience as a data scientist / analytics engineer in high-growth B2B SaaS, preferably supporting sales, CSG or other go-to-market stakeholders. Demonstrated business acumen with a deep understanding of Enterprise Sales strategies (sales pipeline, forecast models, sales capacity, sales segmentation, quota planning), CSG strategies (customer churn risk model, performance attribution) and Enterprise financial metrics (ACV, ARR, NDR) Familiar with CRM platforms (i.e., Salesforce) Technical Proficiency: 6+ years of experience working with SQL in modern data platforms, such as Databricks, Snowflake, Redshift, BigQuery 6+ years of experience working with Python or R for analytics or data science projects 6+ years of experience building business facing dashboards and data models using modern BI tools like Looker, Tableau, etc. Proficient-level experience developing automated solutions to collect, transform, and clean data from various sources, by using tools such as dbt, Fivetran Proficient knowledge of data science models, such as regression, classification, clustering, time series analysis, and experiment design Hands-on experience with batch LLM pipeline is preferred Excellent communication skills to present findings to both technical and non-technical audiences. Passionate to thrive in a dynamic environment. That means being flexible and willing to jump in and do whatever it takes to be successful. Airtable is an equal opportunity employer. We embrace diversity and strive to create a workplace where everyone has an equal opportunity to thrive. We welcome people of different backgrounds, experiences, abilities, and perspectives. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status or any characteristic protected by applicable federal and state laws, regulations and ordinances. Learn more about your EEO rights as an applicant. VEVRAA-Federal Contractor If you have a medical condition, disability, or religious belief/practice which inhibits your ability to participate in any part of the application or interview process, please complete our Accommodations Request Form and let us know how we may assist you. Airtable is committed to participating in the interactive process and providing reasonable accommodations to qualified applicants. Compensation awarded to successful candidates will vary based on their work location, relevant skills, and experience. Our total compensation package also includes the opportunity to receive benefits, restricted stock units, and may include incentive compensation. To learn more about our comprehensive benefit offerings, please check out Life at Airtable. For work locations in the San Francisco Bay Area, Seattle, New York City, and Los Angeles, the base salary range for this role is:$179,500-$221,500 USDFor all other work locations (including remote), the base salary range for this role is:$161,500-$199,300 USD Please see our Privacy Notice for details regarding Airtable's collection and use of personal information relating to the application and recruitment process by clicking here. 🔒 Stay Safe from Job Scams All official Airtable communication will come from an @airtable.com email address. We will never ask you to share sensitive information or purchase equipment during the hiring process. If in doubt, contact us at ***************. Learn more about avoiding job scams here.

A leading data analytics firm in Los Angeles is seeking a Data Scientist to enhance their AdEngage platform and measure ad effectiveness. The ideal candidate has over 3 years of experience in coding with Python, model tuning, and SQL proficiency. Offering a competitive salary and flexible time off, this role supports a hybrid working environment with a focus on innovation in advertising analytics. #J-18808-Ljbffr

The fastest path to relevant recommendations and search Shaped is the fastest path to relevant recommendation and search systems. We help companies turn their behavioral data into truly relevant product and website experiences. We're a Series A companies based in Brooklyn, New York and backed by top investors from Madrona, Y-Combinator and executives from Meta, Google, Amazon and Uber! Job Description Skills: ML, Python, SQL We're looking for a Senior Data Scientist to help customers integrate and develop recommendation models using the Shaped Platform. Responsibilities include connecting external data sources to Shaped, creating ranking models with our declarative SQL interface, and helping customers achieve their business objectives. As a founding Senior Data Scientist, you'll collaborate with a diverse range of customers to solve their ranking challenges. Additionally, you'll contribute to shaping our product roadmaps and engineering culture. We're excited to work with you. Come build the future of AI with us! Qualifications Past experience working with recommendation systems in production Bachelor's in computer science, data science or mathematics related field. Master's degree or PhD will be advantageous. 3+ years of industry experience in a software engineering, data science or solutions architecture role Proficient with Python, SQL Have the willingness to wear many hats, be passionate about unblocking issues for customers, and have an excitement for problem-solving In-depth knowledge of mathematics, statistics and algorithms. Operate well within fast paced, small teams Excellent written and verbal communication skills. Responsibilities Become an expert at using the Shaped ranking platform Experiment with ranking models for customer's discovery use-cases Analyze data to identify performance improvements for customers' models swiftly Experiment with pre-trained image, language, audio and video embedding models that understand our customer's discovery data Build strong relationships with customers' technical teams and leaders to ensure long-term success with Shaped Deliver technical demos to showcase the Shaped's capabilities to customers. Proactively communicate with customers on timelines, updates and next steps Technology Customers typically use Shaped as follows: Connect your data stack, e.g. data warehouse, database or analytics applications Define your model. This includes your optimization objective (e.g. clicks vs purchases vs shares), item and user catalogs, feature types and model types. Consume your results from our real-time, scalable ranking endpoints Evaluate uplift and model results on our dashboard. To power all of this, under the hood, we've built a multi-tenanted, real-time machine learning architecture which automatically sets-up and ingests data both in real-time and batch, transforms data and stores it into our proprietary feature/vector store. Ranking models are continuously optimized and fine-tuned based on real-time feedback ensuring customers are seeing the most relevant and up-to-date results possible. From a machine-learning perspective we use state-of-the‑art large scale neural encoding models to understand multi-modal data types such as image, text, audio and tabular data. We provide an exhaustive library of retrieval, ranking and ordering algorithms which are selected based on the specified model definition. #J-18808-Ljbffr