Data scientist jobs in Fresno, TX

About the Role The Senior Data Engineer will play a critical role in building and scaling an enterprise data platform to enable analytics, reporting, and operational insights across the organization. This position requires deep expertise in Snowflake and cloud technologies (AWS or Azure), along with strong upstream oil & gas domain experience. The engineer will design and optimize data pipelines, enforce data governance and quality standards, and collaborate with cross-functional teams to deliver reliable, scalable data solutions. Key Responsibilities Data Architecture & Engineering Design, develop, and maintain scalable data pipelines using Snowflake, AWS/Azure, and modern data engineering tools. Implement ETL/ELT processes integrating data from upstream systems (SCADA, production accounting, drilling, completions, etc.). Architect data models supporting both operational reporting and advanced analytics. Establish and maintain frameworks for data quality, validation, and lineage to ensure enterprise data trust. Platform Development & Optimization Lead the build and optimization of Snowflake-based data warehouses for performance and cost efficiency. Design cloud-native data solutions leveraging AWS/Azure services (S3, Lambda, Azure Data Factory, Databricks). Manage large-scale time-series and operational data processing workflows. Implement strong security, access control, and governance practices. Technical Leadership & Innovation Mentor junior data engineers and provide technical leadership across the data platform team. Research and introduce new technologies to enhance platform scalability and automation. Build reusable frameworks, components, and utilities to streamline delivery. Support AI/ML initiatives by delivering production-ready, high-quality data pipelines. Business Partnership Collaborate with stakeholders across business units to translate requirements into technical solutions. Work with analysts and data scientists to enable self-service analytics and reporting. Ensure data integration supports regulatory and compliance reporting. Act as a bridge between business and technical teams to ensure alignment and impact. Qualifications & Experience Education Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field. Advanced degree or relevant certifications (SnowPro, AWS/Azure Data Engineer, Databricks) preferred. Experience 7+ years in data engineering roles, with at least 3 years on cloud data platforms. Proven expertise in Snowflake and at least one major cloud platform (AWS or Azure). Hands-on experience with upstream oil & gas data (wells, completions, SCADA, production, reserves, etc.). Demonstrated success delivering operational and analytical data pipelines. Technical Skills Advanced SQL and Python programming skills. Strong background in data modeling, ETL/ELT, cataloging, lineage, and data security. Familiarity with Airflow, Azure Data Factory, or similar orchestration tools. Experience with CI/CD, Git, and automated testing. Knowledge of BI tools such as Power BI, Spotfire, or Tableau. Understanding of AI/ML data preparation and integration.

Python Data Engineer - Houston, TX (Onsite Only) A global energy and commodities organization is seeking an experienced Python Data Engineer to expand and optimize data assets that support high-impact analytics. This role works closely with traders, analysts, researchers, and data scientists to translate business needs into scalable technical solutions. The position is fully onsite due to the collaborative, fast-paced nature of the work. MUST come from an Oil & Gas organization, prefer commodity trading firm. CANNOT do C2C. Key Responsibilities Build modular, reusable Python components to connect external data sources with internal tools and databases. Partner with business stakeholders to define data ingestion and access requirements. Translate business requirements into well-designed technical deliverables. Maintain and enhance the central Python codebase following established standards. Contribute to internal developer tools and ETL frameworks, helping standardize and consolidate core functionality. Collaborate with global engineering teams and participate in internal Python community initiatives. Qualifications 7+ years of professional Python development experience. Strong background in data engineering and pipeline development. Experience with web scraping tools (Requests, BeautifulSoup, Selenium). Hands-on Oracle/PL SQL development, including stored procedures. Strong grasp of object-oriented design, design patterns, and service-oriented architectures. Experience with Agile/Scrum, code reviews, version control, and issue tracking. Familiarity with scientific computing libraries (Pandas, NumPy). Excellent communication skills. Industry experience in energy or commodities preferred. Exposure to containerization (Docker, Kubernetes) is a plus.

We are looking for a talented and motivated Python Data Engineers. We need help expanding our data assets in support of our analytical capabilities in a full-time role. This role will have the opportunity to interface directly with our traders, analysts, researchers and data scientists to drive out requirements and deliver a wide range of data related needs. What you will do: - Translate business requirements into technical deliveries. Drive out requirements for data ingestion and access - Maintain the cleanliness of our Python codebase, while adhering to existing designs and coding conventions as much as possible - Contribute to our developer tools and Python ETL toolkit, including standardization and consolidation of core functionality - Efficiently coordinate with the rest of our team in different locations Qualifications - 6+ years of enterprise-level coding experience with Python - Computer Science, MIS or related degree - Familiarity with Pandas and NumPy packages - Experience with Data Engineering and building data pipelines - Experience scraping websites with Requests, Beautiful Soup, Selenium, etc. - Strong understating of object-oriented design, design patterns, SOA architectures - Proficient understanding of peer-reviewing, code versioning, and bug/issue tracking tools. - Strong communication skills - Familiarity with containerization solutions like Docker and Kubernetes is a plus

Job Title: Senior Software Engineer / Quant Developer (JG4 Level) Duration: Long-term contract with possibility of extension The Senior Data Engineer will design and build robust data foundations and end-to-end data solutions to enable the business to maximize value from data. This role plays a critical part in fostering a data-driven culture across both IT and business stakeholder communities. The Senior Data Engineer will act as a subject matter expert (SME), lead solution design and delivery, mentor junior engineers, and translate Data Strategy and Vision into scalable, high-quality IT solutions. Key Responsibilities Design, build, and maintain enterprise-grade data foundations and end-to-end data solutions. Serve as a subject matter expert in data engineering, data modeling, and solution architecture. Translate business data strategy and vision into scalable technical solutions. Mentor and guide junior data engineers and contribute to continuous capability building. Drive the rollout and adoption of Data Foundation initiatives across the business. Coordinate change management, incident management, and problem management processes. Present insights, reports, and technical findings to key stakeholders. Drive implementation efficiency across pilots and future projects to reduce cost, accelerate delivery, and maximize business value. Actively contribute to community initiatives such as Centers of Excellence (CoE) and Communities of Practice (CoP). Collaborate effectively with both technical teams and business leaders. Key Characteristics Highly curious technology expert with a continuous learning mindset. Strong data-domain expertise with deep technical focus. Excellent communicator who can engage both technical and non-technical stakeholders. Trusted advisor to leadership and cross-functional teams. Strong driver of execution, quality, and delivery excellence. Mandatory Skills Cloud Platforms: AWS, Azure, SAP - Expert Level ELT: Expert Level Data Modeling: Expert Level Data Integration & Ingestion Data Manipulation & Processing DevOps & Version Control: GitHub, GitHub Actions, Azure DevOps Data & Analytics Tools: Data Factory, Databricks, SQL DB, Synapse, Stream Analytics, Glue, Airflow, Kinesis, Redshift, SonarQube, PyTest Optional / Nice-to-Have Skills Experience leading projects or running a Scrum team. Experience with BPC and Planning. Exposure to external technical ecosystems. Documentation using MkDocs.

Title: Data Analytics Engineer Type: 6 Month Contract (Full-time is possible after contract period) Schedule: Hybrid (3-4 days onsite) Sector: Oil & Gas Overview: You will be instrumental in developing and maintaining data models while delivering insightful analyses of maintenance operations, including uptime/downtime, work order metrics, and asset health. Key Responsibilities: Aggregate and transform raw data from systems such as CMMS, ERP, and SCADA into refined datasets and actionable reports/visualizations using tools like SQL, Python, Power BI, and/or Spotfire. Own the creation and maintenance of dashboards for preventative and predictive maintenance. Collaborate cross-functionally to identify data requirements, key performance indicators (KPIs), and reporting gaps. Ensure high data quality through rigorous testing, validation, and documentation. Qualifications and Skills: Bachelor's degree required. Proficiency in Python and SQL is essential. Knowledge of API rules and protocols. Experience organizing development workflows using GitHub. Familiarity with Machine Learning is a plus. Preference for candidates with experience in water midstream/infrastructure or Oil & Gas sectors. Expertise in dashboard creation using tools like Tableau, Spotfire, Excel, or Power BI. Ability to clearly communicate technical concepts to non-technical stakeholders. Strong organizational skills and a customer-service mindset. Capability to work independently or collaboratively with minimal supervision. Exceptional analytical and problem-solving skills, with a strategic approach to prioritization. Ability to analyze data, situations, and processes to make informed decisions or resolve issues, with regular communication to management. Excellent written and verbal communication skills.

a. Relevant experience to be more than 8-9 years, Strong and proficient in Databricks, DLT (Delta Live Tables) framework and Pyspark, need excellent communication. Thanks Rakesh Pathak | Senior Technical Recruiter Phone: ************ *************************| *************** **********************************************************

I want to do 3 rounds of interviews: Teams virtual tech interview with senior developers Karat screening In person interview with managers and directors 5+ years of experience in data engineering, sql and nosql databases like oracle, sql server, postgres, db2, elastic, mongo db and advanced python skills. Advanced application development experience with implementing business logic utilizing SQL procedures and NOSQL utilities Experience with design and development of scalable and performant processes Expert in Python development and fast API microservices what IDEs and tools did they use to code and test? Development experience with real time user interactive applications and communicate between UI and database what protocols/data formats did they use to interact between db and UI

Job Title: Python Data Engineer Experience & Skills 5+ years in Data Engineering with strong SQL and NoSQL database skills: Databases: Oracle, SQL Server, Postgres, DB2, Elasticsearch, MongoDB Advanced Python development and FastAPI microservices experience Application development experience implementing business logic via SQL stored procedures and NoSQL utilities Experience designing scalable and performant processes: Must provide metrics: transactions/day, largest DB table size, concurrent users, API response times Real-time interactive applications with UI-to-database communication: Must explain protocols and data formats used (e.g., JSON, REST, WebSockets) Experience using LLM models, coding agents, and testing agents: Provide specific examples of problem-solving Ability to handle support and development simultaneously: Detail daily split between support and development, ticketing system usage, or direct user interaction Bachelor's degree in Computer Science or relevant major Strong analytic skills, AI tool usage, multitasking, self-management, and direct collaboration with business users Not a Good Fit Experience limited to ETL / backend processes / data transfer between databases Experience only on cloud platforms (Azure, AWS, GCP) without SQL/NoSQL + Python expertise Dexian stands at the forefront of Talent + Technology solutions with a presence spanning more than 70 locations worldwide and a team exceeding 10,000 professionals. As one of the largest technology and professional staffing companies and one of the largest minority-owned staffing companies in the United States, Dexian combines over 30 years of industry expertise with cutting-edge technologies to deliver comprehensive global services and support. Dexian connects the right talent and the right technology with the right organizations to deliver trajectory-changing results that help everyone achieve their ambitions and goals. To learn more, please visit ******************** Dexian is an Equal Opportunity Employer that recruits and hires qualified candidates without regard to race, religion, sex, sexual orientation, gender identity, age, national origin, ancestry, citizenship, disability, or veteran status.

Staff Data Engineer - Houston, TX or US Remote A Series B funded startup who are building the infrastructure that powers how residential HVAC systems are monitored, maintained, and serviced are looking for a Staff Data Engineer to join their team. What will I be doing: Help architect and build the core data platform that powers the company's intelligence - from ingestion and transformation to serving and analytics Design and implement scalable data pipelines (batch and streaming) across diverse data sources including IoT sensors, operational databases, and external systems Work with high-performance database technologies Define foundational data models and abstractions that enable high-quality, consistent access for analytics, product, and ML workloads Collaborate with AI/ML, Product, and Software Engineering teams to enable data-driven decision-making and real-time intelligence Establish engineering best practices for data quality, observability, lineage, and governance Evaluate and integrate modern data technologies (e.g., Redshift, S3, Spark, Airflow, dbt, Kafka, Databricks, Snowflake, etc.) to evolve the platform's capabilities Mentor engineers across teams What are we looking for: 8+ years of experience as a software or data engineer, including ownership of large-scale data systems used for analytics or ML Deep expertise in building and maintaining data pipelines and ETL frameworks (Python, Spark, Airflow, dbt, etc.) Strong background in modern data infrastructure Proficiency with SQL and experience designing performant, maintainable data models Solid understanding of CI/CD, infrastructure-as-code, and observability best practices Experience enabling ML workflows and understanding of data needs across the model lifecycle Comfort working with cloud-native data platforms (AWS preferred) Strong software engineering fundamentals Excellent communicator What's in it for me: Competitive compensation up to $250,000 dependent on experience and location Foundational role as the first Staff Data Engineer Work hand-in-hand with the Head of Data to design and implement systems, pipelines, and abstractions that make us an AI-native company Apply now for immediate consideration!

********* NO THIRD PARTIES PLEASE******** This is a contract to hire position for a very stable organization. Great teammates and a great opportunity for growth and a long career. I-10 West Houston area location for the company. ****The position is REMOTE; however, I am seeking a local Houston candidate as there will be periodic times to come into the office for team meetings. Texas area candidates that are willing to relocate to Houston or at the very least commit to coming to periodic on-site team meetings. Summary: Seeking a Data Modeler that will be responsible for cleaning up to optimize workflows. This position will require strong hands-on Data Modeler experience. MUST have strong Microsoft Fabric experience, which is a key component for this particular role. Requirements: - 7+ years of Data Modeling experience - 3+ years in data modeling or analytics engineering with strong SQL. - Must have 2-3 years plus of hands-on Microsoft Fabric experience. - Lakehouse/Warehouse, One Lake, Delta tables, Dataflows Gen2 or Pipelines; familiarity with SQL endpoint usage. - Star schemas; fact types (transactional, periodic snapshot, accumulating); bridge tables for M: N; degenerate and junk dimensions. - SCD Type 1/2 with MERGE; effective/expiry dating; handling late-arriving data. - Power BI semantic modeling and DAX - Clean tabular model design; CALCULATE/KEEPFILTERS/USERELATIONSHIP; date intelligence; semi-additive measures; model properties (data types, sort-by, formatting). - Incremental refresh; basic aggregations; RLS. - Define tests (unique/not-null/accepted values), document metrics, manage endorsements; apply sensitivity labels for PII/regulated data. Translate stakeholder requirements into grain/facts/dimensions and certified measures; collaborate across DE, BI, and business teams.

Job Title: Data Modeler II Contract: 12+ Months with Possible Extension Department: SCM Enablement & Innovation - SCM team enabling and innovate - enable to innovate key misconception is they are from the business, they are not an IT group, and they are managing innovations on the business side. This role will involve creating solutions, will not be a power BI development role. Presenting and creating solutions for client - we as a team attempt to solve enterprise solutions with business teams and develop some of those solutions for small and medium problems for low code solutions core ERP system client is using is Oracle Cloud Responsibilities: Need someone who has a depth of AI understanding - have a good understanding of python in terms of data transformations, project management, understanding requirements, and gathering data Must do user acceptance testing and deployment Ability to oversee projects they are working on and plan ahead without needing that guidance/instruction - ability to be proactive Providing end to end solutions Gathering data from ERP system, putting into data verse, creating prompts, etc. Gathering pain points from customers and need to discuss with team on how to solve that problem Reviewing anything else outside of ERP to massage and present to customers/stakeholders and provide solutions to their problems Data bricks (good knowledge needed), data verse and API connection between ERP and Oracle Platforms Using power automate/power apps Translate business to technical terms and vice versa Skills: Need someone who has a depth of AI understanding - have a good understanding of python in terms of data transformations, project management, understanding requirements, and gathering data Knowledge of implementing solutions using data bricks would be valuable Should have good understanding end to end user enterprise and how the user should interact with local platforms Good understanding of Oracle Cloud 50/50 technical/business oriented - DOES NOT want someone super technical who cannot speak on behalf of the business Some knowledge in supply chain OR oil & gas industry needed Experience cleaning data is a huge plus

Must Haves: Strong proficiency in Python; 5+ years' experience. Expertise in Fast API and microservices architecture and coding Linking python based apps with sql and nosql db's Deployments on docker, Kubernetes and monitoring tools Experience with Automated testing and test-driven development Git source control, git actions, ci/cd , VS code and copilot Expertise in both on prem sql dbs (oracle, sql server, Postgres, db2) and no sql databases Working knowledge of data warehousing and ETL Able to explain the business functionality of the projects/applications they have worked on Ability to multi task and simultaneously work on multiple projects. NO CLOUD - they are on prem Day to Day: Insight Global is looking for a Python Data Engineer for one of our largest oil and gas clients in Downtown Houston, TX. This person will be responsible for building python-based relationships between back-end SQL and NoSQL databases, architecting and coding Fast API and Microservices, and performing testing on back-office applications. The ideal candidate will have experience developing applications utilizing python and microservices and implementing complex business functionality utilizing python.

# **Data Scientist \- Energy Trading** **Company:** Expand Energy Our core values - Stewardship, Character, Collaborate, Learn, Disrupt - are the lens through which we evaluate every business decision\. As a dynamic, growing company that offers extremely competitive compensation and benefits, our employees are our most valued assets and the foundation of Expands performance among our E&P competitors\. We seek applicants from all backgrounds to ensure we get the best, most creative talent on our team\. We realize that, historically, underrepresented groups feel the need to be 100% qualified in order to apply\. If you meet any combination of our requirements, we encourage you to apply\. We strive to hire people from a wide variety of backgrounds, not just because it's the right thing to do, but because it makes our company stronger\. ## **Job Summary** This isn't about maintaining existing systems \- you'll be architecting the analytical foundation that spots major market shifts or dislocations and drives real commercial value\. You'll lead the development of sophisticated models and analytical frameworks across natural gas, LNG, power, and related commodities while shaping the data strategy that supports critical trading decisions\. The role combines hands\-on advanced modeling with strategic thinking about data acquisition and architecture, with the autonomy to steer the ship and move quickly as both you and the business scale up\. Reporting structure within Fundamental & Quantitative Analytics team will be determined based on team composition and individual experience levels\. ## **Job Duties & Responsibilities** + Lead end\-to\-end advanced modeling initiatives from identifying data needs and acquisition strategies \(vendor sources, web scraping, internal systems, unstructured data\) through to deployment of production models + Develop and implement sophisticated analytical techniques including machine learning, time series forecasting, optimization models, and statistical analysis to address critical business themes with speed and accuracy + Serve as the technical visionary for applying novel analytical techniques and emerging technologies including machine learning, artificial intelligence, and large language models to energy commodity challenges + Collaborate closely with the Lead Data Engineer to develop integrated data strategy that supports both current analytical needs and cutting\-edge technological applications + Collaborate closely with data engineers and analysts to translate complex business requirements into technical data solutions, ensuring seamless integration from data acquisition to model deployment + Drive rapid response capabilities for market analysis, developing models and insights that can quickly adapt to changing market conditions and emerging opportunities + Build and maintain advanced analytical outputs including predictive models, risk assessment tools, optimization algorithms, and real\-time monitoring systems + Automate and streamline analytic processes and products + Establish best practices for modeling processes \(e\.g\. technical documentation, code review, version control, etc\.\) + Partner with the Director and analytics team members, traders, and commercial stakeholders to identify high\-impact analytical opportunities and translate findings into actionable business intelligence + Contribute to establishing best practices for model development, validation, and deployment while mentoring junior team members on advanced analytical techniques ## **Job Specific Skills** + Strong background in machine learning, statistical modeling, optimization, and time series analysis with proven ability to apply these techniques to real\-world business problems + Proficiency with advanced analytical tools including Python/R, SQL, machine learning frameworks \(scikit\-learn, TensorFlow, PyTorch\), and cloud computing platforms + Experience with diverse data acquisition and integration methods including APIs, web scraping; database management, schema development, and application of metadata layers; and working with both structured and unstructured data sources + Strong understanding of data architecture principles and ability to contribute to strategic decisions about data storage, processing, and modeling infrastructure, including cloud compute solutions \(Snowflake experience preferred but not required\) + Energy commodity market knowledge or demonstrated ability to quickly develop deep domain expertise in complex technical markets + Excellent communication skills with ability to translate complex analytical concepts into clear business insights for both technical and non\-technical stakeholders ## **Education** Minimum: High school diploma or GED Preferred: Bachelor's degree \- from accredited university \- Mathematics, Statistics, Analytics, Engineer, Computer Science, or related field Preferred: Master's degree \- from accredited university ## **Experience** Minimum: 2 \- 5 years related work experience Prior or current data science, quantitative analysis, or related technical roles with demonstrated expertise in advanced modeling techniques ## **Additional Qualifications** + Natural Gas Market Experience: Experience with natural gas market fundamentals including basis trading, pipeline systems, storage dynamics, and location\-specific pricing datasets\. Candidates from adjacent markets \(power, crude oil, financial commodities\) with strong analytical aptitude will be considered + Energy Trading Background: Experience at energy trading firms, commodity companies, or related commercial energy organizations with understanding of market dynamics and trading applications + Advanced Technical Skills: Experience with optimization software \(Gurobi, CPLEX\), advanced time series methods, or specialized domain modeling techniques + Data Strategy Experience: Track record of contributing to or leading data architecture decisions, platform selection, or analytical infrastructure development + Cross\-Functional Leadership: Experience working across technical and business teams to drive analytical initiatives from conception to implementation + Real\-Time Analytics: Experience developing models and systems that support time\-sensitive business decisions or trading applications + Emerging Technologies: Experience with or strong interest in applying novel technologies including large language models, advanced AI techniques, or cutting\-edge analytical methods to business applications Expand Energy takes necessary action to ensure that all applicants are treated without regard to their race, color, religion, sex, sexual orientation, age, gender identity, national origin, genetic information, disability, pregnancy, military or veteran status or any other protected characteristic as established by law\. Expand Energy Corporation's operations are focused on discovering and developing its large and geographically diverse resource base of unconventional oil and natural gas assets onshore in the United States\. **Nearest Major Market:** Houston **Job Segment:** Pipeline, Cloud, Data Architect, Quantitative Analyst, Statistics, Energy, Technology, Data

Job Title: Data Scientist The Chord Energy Data Scientist role is a technical individual contributor role, focused on supporting business opportunities through the use of exploratory data analytics, machine learning models and generative AI opportunities. This position is located in Downtown Houston, TX. Hybrid work schedule is an option for remote work on Mondays and Fridays. Level and salary commensurate with experience. Essential Job Functions The primary responsibility involves leading and participating in multi-disciplinary projects aimed at providing business solutions to a diverse set of problems ranging from, but not limited to, production automation/optimization, drilling and completion process optimization, back-office process improvement and automation, dashboard generation and deployment, and computer vision aided operations. Additionally, the Data Scientist will contribute to the adoption of new technologies and best practices for analytical workflows. The ability to work well in a team and in support of core business functions will be critical to the success of this role. This job description is not intended to be an all-inclusive list of duties and responsibilities of the position. Incumbents will be required to follow any other job-related instructions and duties outside of their normal responsibilities as assigned by their supervisor. Minimum Qualifications * Master's or Bachelor's degree in Data Science, Computer Science, or related field * 5+ years in data science/ML (including time-series, geospatial, and predictive modeling) * Proven experience and/or education in data analytics and management of large datasets * Proficiency in Python (pandas, scikit-learn) and SQL; experience with Azure ML/MLflow and deploying models to production. * Domain familiarity with upstream oil & gas workflows (subsurface and operations) and the ability to translate expert knowledge into features and experiments. * Strong interpersonal and collaborative skills * Demonstrated ability to work in a team-oriented environment * Excellent presentation skills * Ability to work in a fast-paced and fluid environment; flexible with the demands of a growing company * Strong coaching, prioritization, and stakeholder-management skills; able to convert business problems into robust, scalable model solutions and communicate outcomes clearly. * Ability to meet deadlines * Physical Requirements and Working Conditions: Must possess mobility to work in a standard office setting and to use standard office equipment, including a computer, stamina to maintain attention to detail despite interruptions, strength to lift and carry files weighing up to 10 pounds; vision to read printed materials and a computer screen, and hearing and speech to communicate in person and over the telephone The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Preferred Qualifications * Master's degree or PHD or certification in Data Science or Data Analytics * Familiarity with additional programming languages (SQL, R, C++, etc.) * Previous Oil and Gas operator experience * Exposure to Petroleum Engineering and Geoscience workflows * Exposure to the energy sector, particularly unconventional exploitation programs This role presents an exciting opportunity for a data scientist to contribute to the advancement of Chord's data science transformation, leveraging expertise in data analytics to drive innovation and optimize operational outcomes. EEO Statement: Chord Energy does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factor.

The Associate Data Scientist's primary responsibility will be to assist in the computational analysis of spatial single-cell transcriptomic and proteomic data from patient tumors generated from platforms such as CosMx Spatial Molecular Imager. Analyses will involve identifying spatially localized cellular niches, characterizing immune and epithelial cell states, modeling cell-cell communication, and uncovering pathways through which host-microbe interactions influence tumor biology. The ideal candidate will have experience in cancer biology omics. At MD Anderson, we offer careers built on care, growth, and balance. Our employees enjoy a benefits package designed to support every stage of life, starting on day one. · Paid employee medical benefits (zero premium) starting on first day for employees who work 30 or more hours per week · Group Dental, Vision, Life, AD&D and Disability coverage · Paid time off (PTO) and Extended Illness Bank (EIB) paid leave accruals Paid institutional holidays, wellness leave, childcare leave, and other paid leave programs · Tuition Assistance Program after six months of service · Teachers Retirement System defined-benefit pension plan and two voluntary retirement plans · Employer paid life, AD&D and an illness-related reduced salary pay program Extensive wellness, recognition, fitness, employee health programs and employee resource groups Key Functions 1. Analyzation and Integration Single-Cell and Spatial Omics Data Process and interpret single-cell RNA-seq and spatial proteomic and transcriptomic datasets to identify cellular states and tumor microenvironment features. Integrate multimodal data from platforms such as CosMx, MIBI, STOmics or GeoMx to uncover spatial niches and model cell-cell and host-microbe interactions. Apply analytical methods including clustering, differential expression, trajectory inference, and spatial proximity analyses. 2. Computational Pipelines for Biological Insight Development Build, document, and maintain reproducible analysis pipelines in Python and R for high-dimensional omics datasets. Conduct pathway enrichment and network-based analyses to identify biologically relevant trends in cancer and immune responses. Generate publication-ready visualizations and figures that communicate key findings for manuscripts, grants, and presentations. 3. Collaborate, Communicate, and Document Research Outputs Partner with interdisciplinary team members to interpret data, support experimental planning, and contribute to scientific publications. Present analytical results in lab meetings and project discussions to inform ongoing research directions. Maintain well-organized code, metadata, and supplementary materials to support reproducibility and data sharing. Education Required: Bachelor's degree in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Statistics, Computer Science, Computational Biology, or related field. Experience Required: Two years experience in scientific software or industry development/analysis. Preferred: Knowledge of transcriptomics and proteomics is a plus The University of Texas MD Anderson Cancer Center offers excellent benefits, including medical, dental, paid time off, retirement, tuition benefits, educational opportunities, and individual and team recognition. This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment. It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state, or local laws unless such distinction is required by law.************************************************************************************************ Additional Information

Role: Data Scientist Role : 6 months Job Details: Must Have Skills (Top 2 technical skills only) Minimum 8 years of relevant experience in applying data mining, artificial intelligence, signal processing, machine learning, optimization etc. in business analytics or scientific/engineering settings Experience with statistical software, scripting languages, tools, and platforms (e.g., R, Python, Hadoop etc.) Nice to have skills (Top 2 only) A demonstrated ability to solve challenging business problems using a data science approach by developing novel and/or adapting existing computational methods Strong skills in communicating and presenting data-derived insights to non-technical audiences appropriately. Additional Information Thanks & Regards Praveen K. Paila ************

Brief Description: NexTier's Completions Data Science team brings together talented, driven professionals who turn complex operational data into clear insights and empower our organization to make smarter, data-backed decisions every day. You will work specifically with Operations and Maintenance departments to develop physics-driven models and reliability frameworks that predict equipment behavior and optimize maintenance strategies for our frac fleet. Detailed Description: In this role you will collaborate with Program Managers to lead the strategy and execution of hybrid physics and machine-learning models for equipment reliability. You will design and run first-principles simulations, integrate high-frequency telemetry into digital twins, deploy scalable model pipelines in the cloud and validate predictions against field data. Key Responsibilities: Define and guide the development of physics-ML reliability models (Weibull analysis, survival modeling, FMEA) Perform fluid-mechanics and mechanical simulations in Python or MATLAB and integrate outputs with telemetry streams Architect, deploy and monitor model training and serving pipelines on GCP AI Platform or Dataiku Establish validation protocols by coordinating with subject-matter experts to calibrate model assumptions Partner with maintenance, operations and field teams to align modeling efforts with business needs and data availability Identify new digital-twin use cases and build proof-of-concepts for early-warning systems and maintenance optimization Present technical findings to operations leadership, maintenance planners and engineering management Job Requirements: Prior experience in equipment reliability, predictive maintenance or physics-based modeling in oil and gas Expert programming skills in Python (SciPy, NumPy) for simulation and model development Strong foundation in reliability engineering methods such as Weibull analysis, survival modeling and FMEA Strong communication skills with the ability to explain complex models to non-technical stakeholders Ability to manage multiple priorities and deliver results on time Minimum Qualifications: Bachelor's degree in Mechanical Engineering, Petroleum Engineering, Physics or related field 5+ years of experience applying physics-based modeling or reliability engineering in industrial settings 3+ years building and deploying data-science algorithms on cloud platforms (AWS, GCP or Azure) 3+ years developing simulation code in Python Preferred Qualifications: Master's degree or higher in a quantitative engineering or physical science discipline Research publications or patents in equipment reliability, preventative maintenance or related areas Prior field experience in equipment maintenance Experience integrating physics-based models with machine-learning frameworks such as TensorFlow or PyTorch Working Condition: Work is primarily in a climate controlled / office environment with minimal safety / health hazard potential. The employee is regularly required to sit, stand, or walk with occasional lifting (overhead, waist level) from floor, bending and frequent near vision use for reading and use of computer, telephone, and other office equipment.

About GivingTuesday GivingTuesday is a global generosity movement unleashing the power of people and organizations to transform their communities and the world. The organization works with partners across sectors and borders to understand the drivers and impacts of generosity, explore giving behaviors and patterns, and use data to inspire more giving around the world. GivingTuesday offers the largest philanthropic data collaborative effort in the social sector - with unique, granular datasets from a wide range of organizations featuring key sector information As we scale up, we are expanding our team of data scientists, researchers and engineers, who will continue to grow and improve our unique data assets, methodologies, and technical infrastructure. In pursuit of the goals and expansion of the data commons, GivingTuesday partners with key organizations to leverage their expertise to manage and lead different aspects of the work. These data & technology partners (DARO, With Intent) manage staff, projects, and ongoing functions for the data commons with dedicated staff embedded in GivingTuesday in those capacities in cross-functional roles. This role is one of these positions - managed by our partner organizations but embedded in GivingTuesday's Data Team. Data Scientist Our global data science team works on a diverse set of problems and projects related to learning, insights, and impact measurement in the nonprofit sector. We are looking for a Data Scientist to join our growing team, where they will work with data engineers, analysts, and other team members to develop compelling and useful knowledge products for GivingTuesday stakeholders, including academics, data partners, the social/nonprofit sector, and the general public. In this role you will: Work with a wide range of data types including donation data, transaction records, government and census data, nonprofit tax filings, survey data on perceptions and activity, and philanthropic investment account data, gathered from collaborators and institutional partners in the nonprofit ecosystem Develop quarterly reports on sector-wide trends in monetary giving using transaction records Enhance core data and analytical pipelines by improving data quality validation, automating recurring processes, and implementing methodological updates in workflows to support evolving analytical needs Deliver and write analyses with actionable insights and communicate these findings to cross functional stakeholders of varying technical levels Manage key datasets and improve their usability by creating database dictionaries and user documentation Create impactful data visualisations and interactive data dashboards for stakeholders We are looking for someone with: Demonstrated interest in the nonprofit and philanthropic sector and use of data to promote better social outcomes Advanced analytical skills in a research context, conducting exploratory analysis and mapping data flows, integration of datasets, and reviewing data sources and tools Experience with statistical methods including hypothesis testing, regression analysis, and sampling techniques for the purposes of social science research (such as economics, mixed methods) and/ or business analytics Experience working with scripting languages (Python required) and data querying languages (SQL preferred) Solid data visualisation skills and an aptitude for translating technical outputs into compelling stories Experience with software development tools and practices (e.g. version control, testing outputs, and applying QA processes) Understanding of legislation around privacy and best practices for securing data Solid relationship management skills, with the ability to collaborate with a variety of internal and external stakeholders on complex research initiatives Outstanding written and oral communication skills in English and an ability to communicate clearly and directly Attention to detail and ability to synthesise diverse datasets GivingTuesday is actively seeking candidates with unique and diverse work backgrounds to grow our team. We are especially excited to talk to you if have: Programming skills: Python, PySpark, SQL, Databricks, Git, pandas Experience developing and maintaining analytical pipelines, including closely collaborating with Data Engineering teams Advanced Modelling: Regressions, Clustering, Dimensionality Reduction, Classification, Bayesian, Time-Series Analysis, prompt engineering Experience working with data platforms such as Databricks (or other forms of cloud data lakes/warehouses/lakehouses) Experience building data exploration tools using code-based frameworks (such as R Shiny or Streamlit, for example) An advanced degree in a quantitative research-field (definitely not required!). Non-degreed candidates must possess an extensive public record of competent, curiosity-driven data exploration on github, huggingface, kaggle, stackoverflow or similar. Location & Work Hours Remote. We are happy to consider applicants based in countries outside of where this is posted. This is a full-time position. We are looking for candidates who can overlap with a 9:00 to 5:00 EST work-day, with some flexibility. Compensation Our compensation is competitive and tailored to align with cost-of-living differences across various regions. We look forward to meeting candidates from diverse backgrounds who can bring unique perspectives to our team! For applicants in the US, our expected salary range is $50,000 to $70,000 USD per year. Application Guidelines GivingTuesday is committed to a work environment where our employees feel included, valued, and heard. If you require any accessibility accommodation in the interviewing process please let us know. We know that applying for a job takes a lot of time and energy and we treat every application with care and attention. Only those applicants who are selected will be contacted. To apply, please provide your resume and a short cover letter describing your interest in the position. We want to hear from you, in your own words. Submissions that reflect your personal perspective will stand out more than those written by AI tools.

DPR Construction is seeking a skilled Senior Data Scientist to help advance our data-driven approach to building. In this role, you'll use statistical analysis, machine learning, and data visualization to turn complex construction and business data into actionable insights that improve project planning, cost forecasting, resource management, and safety. Working with project and operations teams, you'll build and deploy scalable, secure data solutions on cloud platforms like Azure and AWS, driving innovation and operational excellence across DPR's projects. Responsibilities * Data analysis and modeling: Analyze large datasets to identify trends, bottlenecks, and areas for improvement in operational performance. Build predictive and statistical models to forecast demand, capacity, and potential issues. * Develop and deploy models: Build, test, and deploy machine learning and AI models to improve operational processes. * Analyze operational data: Examine data related to projects, production, supply chains, inventory, and quality control to identify patterns, trends, and inefficiencies. * Optimize processes: Use data-driven insights to streamline workflows, allocate resources more effectively, and improve overall performance. * Forecast and predict: Create predictive models to forecast outcomes, such as demand, and inform strategic decisions. * Communicate findings: Present findings and recommendations to stakeholders through reports, visualizations, and presentations. * Ensure reliability: Build and maintain reliable, scalable, and efficient data science systems and processes. * Collaboration: Partner with project managers, engineers, and business leaders to ensure data solutions are aligned with organizational goals and deliver tangible improvements. * Continuous Learning: Stay current with advancements in data science and machine learning to continually enhance the company's data capabilities. * Reporting and communication: Create dashboards and reports that clearly communicate performance trends and key insights to leadership and other stakeholders. Translate complex data into actionable recommendations. * Performance monitoring: Implement data quality checks and monitor the performance of models and automated systems, creating feedback loops for continuous improvement. * Experimentation: Design and evaluate experiments to quantify the impact of new systems and changes on operational outcomes. Qualifications * Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Engineering, or a related field. * 7+ years of experience in data science roles within AEC, product or technology organizations. * At least 4 years of experience working with cloud platforms, specifically Azure and AWS, for model deployment and data management. * Strong proficiency in Python or R for data analysis, modeling, and machine learning, with experience in relevant libraries (e.g., Scikit-learn, TensorFlow, PyTorch) and NLP frameworks (e.g., GPT, Hugging Face Transformers). * Expertise in SQL for data querying and manipulation, and experience with data visualization tools (e.g., Power BI, Tableau). * Solid understanding of statistical methods, predictive modeling, and optimization techniques. * Expertise in statistics and causal inference, applied in both experimentation and observational causal inference studies. * Proven experience designing and interpreting experiments and making statistically sound recommendations. * 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. * Experience working with construction-related data or similar industries (e.g., engineering, manufacturing) is a plus. Preferred Skills * Familiarity with construction management software (e.g., ACC, Procore, BIM tools) and knowledge of project management methodologies. * Hands-on experience with Generative AI tools and libraries. * Background in experimentation infrastructure or human-AI interaction systems. * Knowledge of time-series analysis, anomaly detection, and risk modeling specific to construction environments. DPR Construction is a forward-thinking, self-performing general contractor specializing in technically complex and sustainable projects for the advanced technology, life sciences, healthcare, higher education and commercial markets. Founded in 1990, DPR is a great story of entrepreneurial success as a private, employee-owned company that has grown into a multi-billion-dollar family of companies with offices around the world. Working at DPR, you'll have the chance to try new things, explore unique paths and shape your future. Here, we build opportunity together-by harnessing our talents, enabling curiosity and pursuing our collective ambition to make the best ideas happen. We are proud to be recognized as a great place to work by our talented teammates and leading news organizations like U.S. News and World Report, Forbes, Fast Company and Newsweek. Explore our open opportunities at ********************