Data scientist jobs in Houston, 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.

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.

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 Aatmesh *************************

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!

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

********* 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.

SCM Enable & Innovate is seeking a Data Modeler II with a product-driven, start-up mindset to support end-to-end development of innovative data solutions that drive measurable business value across Supply Chain operations. This role will work in a hybrid model based in Houston, TX and requires strong expertise in data science, analytics, ETL development, and product execution within the oil & gas industry. Responsibilities Product Development Develop innovative data science solutions leveraging deep knowledge of the oil & gas industry and Supply Chain processes. Design and optimize ETL pipelines for scalable, high-performance data processing using Azure Databricks, Microsoft Dataflow, Dataverse, and/or Oracle Autonomous Data Warehouse (ADW). Work with various ERP systems, including SAP and Oracle, along with their analytics tools to enable data-driven decisions. Integrate solutions with enterprise data platforms and visualization tools for reporting. Build and maintain master datasets to support procurement, spend analytics, and market intelligence. Ensure adherence to data governance, security, and company policies across all development efforts. Program Management Define and document project objectives, problem statements, business value, business processes, and requirements. Manage project timelines, resources, and cross-functional coordination to ensure alignment with project goals. Facilitate project meetings and communicate progress updates to stakeholders. Maintain all project documentation, including idea assessments, requirements, design documents, and weekly status reports. Communicate technical details, requirements, and design elements to internal business stakeholders in clear, understandable language. Skills & Qualifications Experience 5-7 years of relevant experience in Supply Chain Management (SCM) or product development. Technical Expertise Advanced proficiency in data science, including statistical analysis, predictive analytics, text-based sentiment analysis, machine learning, and data visualization. Strong experience working with unstructured data, such as PO line descriptions and customer feedback. Advanced proficiency in Python and PySpark with Databricks for large-scale data processing. Hands-on experience with prompt engineering. Experience developing solutions using the Microsoft Power Platform (Copilot Studio, Dataflow, Dataverse, Power Automate, Model-Driven Apps). In-depth understanding of SAP and Oracle Cloud modules (SCM, A/P, Projects, Finance). Proficiency in SQL for data transformation (preferred). Experience using Alteryx for data preparation and workflow automation (preferred). Industry Knowledge Strong understanding of the oil & gas sector, including SCM Procure-to-Pay / Source-to-Pay processes and associated value drivers. Project Management Skilled in agile/waterfall methodologies. Strong stakeholder engagement and communication skills. Proficiency in documentation tools including PowerPoint, Excel, and Visio.

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.

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 ************

Context & Environment TotalEnergies Gas and Power is the trading arm of TotalEnergies, focused on low‑carbon energies including gas, LNG, and power. Operating in fast‑evolving markets, the business must constantly adapt to dynamics shaped by both internal and external factors. Price volatility, supply‑demand imbalances, and broader energy sector shifts-such as climate policies, changes in the energy mix, and the rise of new energy sources-create a complex environment. Within this context, trading plays a critical role in driving growth and profitability across a key segment of the business, supporting TotalEnergies' ambition to achieve carbon neutrality by 2050. Activities Role Overview: Purpose: The position is within the Modelling and Analysis for Trading Strategy (MATS) department, which is responsible for the end-to-end design and development of comprehensive quantitative models, state-of-the-art analytical and AI tools, and research that help optimize trading decisions across all TGP trading desks. Positioned at the strategic interface between Trading, Risk Management and IT, it guarantees the agility, robustness and continuous innovation of the algorithms driving TGP market strategy. Objectives: Develop and maintain high-performance algorithmic and AI-driven quantitative products tailored for trading and energy optimization. The teams' key role is to build and maintain long-lasting frameworks for various advanced use cases (e.g. forecasting, AutoML, optimization, physical dispatch, backtesting, etc.), capable to adapt to diverse trading strategies as well as effectively address complex challenges such as pricing, hedging, trading, transactions, and asset management. The team is committed to driving innovation while delivering enduring product excellence. The team comprises highly skilled data scientists, software and quant developers, with deep domain expertise in energy and commodities markets. Impact: The role directly impacts TGP's trading performance by contributing to long-term P&L growth through scalable, reusable and intelligent solutions that last. Such a role demands strong technical skills, critical thinking and a team spirit Location: Based in Houston, TX Key Responsibilities: * Develop scalable, reusable frameworks that drive long-term P&L growth and adapt to evolving business needs. * Enhance and maintain production-grade solutions, ensuring rapid feature delivery, minimal technical debt, and long-term reliability. * Support analysts, data scientists, and traders by clearly presenting features and guiding effective use of tools. * Collaborate with partner teams to co-develop specialized tools while maintaining architectural standards. * Apply advanced quantitative techniques, build visualization/simulation applications, and promote best development practices. * Document solutions thoroughly and communicate regularly with MATS and trading desks to align with business challenges and opportunities. Candidate Profile Key Qualifications: * Strong technical/engineering background (BEng/MSc in a quantitative field); fluent in English with international/multicultural experience a plus * 3+ years' Python development experience, including scalable, well-tested code, debugging, and refactoring legacy systems; skilled in CI/CD, containerization, databases, APIs, and visualization dashboards * 2+ years' energy trading experience with knowledge of US gas and power markets; capable of developing algorithms for backtesting, portfolio optimization, asset pricing, and dispatch * Solid foundation in data science, machine learning, deep learning, and quantitative algorithms (e.g., time series forecasting, optimization) * Collaborative, adaptable, and innovative team player with clear communication skills; familiar with AWS, Spark, Prefect, Flask, REST, GraphQL, SQL, MongoDB, Plotly/Dash, TensorFlow, and PyTorch Additional Information TotalEnergies values diversity, promotes individual growth and offers equal opportunity careers.

Job Title: Data Scientist Department: Purchasing Reports To: COO Location: 6969 North Fwy, Houston, TX 77076 Employment Type: Full-time We are seeking a highly skilled and analytical Data Scientist to join our Purchasing Department. The successful candidate will leverage data analytics, machine learning, and statistical modeling to optimize procurement processes, forecast demand, and enhance supply chain efficiency. This role requires strong data management skills and collaboration with cross-functional teams to drive data-driven decision-making and cost reduction initiatives. Key Responsibilities: Data Analysis & Reporting: Develop predictive models to forecast demand, optimize inventory levels, and reduce procurement costs. Analyze historical purchasing data to identify trends, inefficiencies, and opportunities for cost savings. Build and maintain data pipelines and dashboards to monitor supplier performance, lead times, and pricing trends. Generate actionable insights and reports for senior management to support strategic decision-making. Machine Learning & Process Optimization: Implement machine learning algorithms to enhance supplier selection and risk assessment. Work with procurement teams to develop data-driven negotiation strategies and supplier recommendations. Automate data collection, cleaning, and reporting processes for improved efficiency. Utilize statistical analysis to assess market trends, raw material costs, and external factors affecting purchasing decisions. Collaboration & System Integration: Work closely with IT and supply chain teams to integrate data solutions with existing ERP and procurement systems. Support cross-functional teams including procurement, inventory management, and supplier relations to ensure smooth data utilization. Qualifications: Education & Experience: Bachelor's degree in Data Science, Statistics, Computer Science, Supply Chain Management, or a related field. At least 2-4 years of experience in data analysis, machine learning, or procurement analytics. Proven experience in data modeling, with strong expertise in statistical analysis and predictive analytics. Skills & Competencies: Proficiency in programming languages such as Python, R, or SQL for data manipulation and analysis. Experience with data visualization tools (e.g., Tableau, Power BI) to present insights effectively. Strong problem-solving and critical-thinking abilities. Excellent communication and interpersonal skills for cross-functional collaboration. Detail-oriented with strong organizational skills and the ability to manage multiple priorities. Preferred: Experience with ERP systems (e.g., SAP, Oracle) and procurement analytics tools. Knowledge of machine learning frameworks and process improvement methodologies (e.g., Lean, Six Sigma). Job Details: Work Schedule: Mon-Fri: 8:00 AM - 5:30 PM Sat: 8:00 AM - 3:00 PM Employee Benefits: Health Benefits: Medical, Vision, and dental coverage (details provided after the initial period). 401k: Eligibility after six months. Vacation Time: 40 hours per year, accrued on a pro-rata basis. Sick Time: 40 hours per year, accrued on a pro-rata basis. Additional Benefits: Employee discounts PAYACTIV Paid Holidays (6 days): New Year's Day Memorial Day Independence Day Labor Day Thanksgiving Day Christmas Day

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.

VERY URGENT AND IMMEDIATE NEED. Note: Need Only US Citizen, Green Card, EAD-GC, J2 EAD, H4 EAD, L2 EAD, and TN Visa. Job Title: Data Scientist Duration: 06+ Months Contract Note: Oil, Gas and energy background in Preferred Job Description: You will work with a team of data engineers and scientists who use data and apply cutting statistical machine learning models to build forecasting models for different energy markets. The entire Data team works collaboratively and is a strong partner for teams across the company. You will get to meet and learn from diverse and talented colleagues. Specific responsibilities include: Analyze energy time series and summarize the statistical properties of energy signals Build predictive models and forecast signals for day-ahead consumption data Evaluate the performance and compare the results with existing models Deploy the best model and document the result of this research Business Skills Excellent verbal, written, and interpersonal communication skills Strong understanding of the product development lifecycles Strong understanding of software development, testing and integration methodologies Personal effectiveness/credibility Strong problem solving and analysis skills Technical Skills Proficiency with Python or R, SQL and familiarity with working in big data environments (2 years minimum) At least 2+ years of experience of deploying machine learning models and frameworks in production At least 3 years of experience with: Experiences in both Supervised and Unsupervised machine learning models (Regressions, Gradient Boosted methods, SVMs, Random Forests, Clustering) Familiar with python packages such as Pandas, SkLearn, Numpy etc Deep learning (CNN, RNN, LSTM) and framework library (e.g., Keras, TensorFlow, PyTorch) and Graph Neural Networks Evaluation and hypothesis testing. At least 3 years of experience with Cloud computing platforms such as AWS, Azure (preferably AWS) Standard concepts and technologies used in CI/CD build and deployment pipelines. At least 2 years of experience in distributed computing frameworks such as Spark or Pyspark is desirable.

Job DescriptionLocation: Houston, TX Clearance: DHS Suitability - nice to have US Citizenship is required Experience: 5+ years Remote/Hybrid/Onsite: 100% Onsite work (non-negotiable) Skill Level DesiredYears ExpSenior5-10Expert11-15Subject Matter Expert16+ Full Time: Direct Hire No 3rd Party Vendors - No exceptions Note: Available Immediately & Benefits posted below Introduction Our client seeks a skilled Data Scientist / Data Engineer to join our team and support the Houston Field Office. In this role, you will analyze large and complex datasets to aid in cybercrime investigations, develop ETL processes, and collaborate closely with cybercrime investigators and forensic analysts to enhance investigative outcomes. Role - Analyze large and complex datasets to identify patterns, anomalies, and trends that can aid in cybercrime investigations. - Utilize advanced statistical methods and algorithms to extract actionable insights from data. - Develop and implement ETL (Extract, Transform, Load) processes to ensure data is efficiently processed and integrated. - Design and optimize data indexing and search processes to facilitate efficient data retrieval and discovery. - Work closely with cybercrime investigators and forensic analysts to provide data-driven insights that enhance investigative outcomes. - Participate in cross-functional teams to integrate data engineering methodologies into ongoing investigations. - Create data visualizations and dashboards to present findings in an easily interpretable manner for both technical and non-technical stakeholders. - Prepare detailed reports and presentations for internal and external audiences. - Contribute to the development and refinement of internal analytics tools and platforms, enhancing the overall effectiveness of data-driven investigations. - Develop prototypes and algorithms to support specific investigative needs. - Understand and apply Large Language Models (LLMs) to traditional Natural Language Processing (NLP) problems. - Utilize LLMs to triage unstructured text and extract relevant information for investigations. - Bachelor's degree in data science, Statistics, Computer Science, or a related field. - Minimum of 5+ years in data analytics or data engineering, preferably with a focus on cybercrime or financial investigations. - Proficiency in programming languages such as Python, R, or similar. - Proficiency with ETL processes and data integration. - Strong knowledge of data indexing, search, and discovery techniques. - Proficiency in database systems and SQL. - Strong analytical and problem-solving skills. - Familiarity with data visualization tools (e.g., Tableau, Power BI). - Excellent communication skills, with the ability to explain complex technical concepts to non-technical audiences. - Ability to work collaboratively in a team environment. - Experience in developing and implementing algorithms and prototypes. - Understanding of Large Language Models (LLMs) and their application to NLP problems. - Experience with traditional NLP techniques and tools. - Experience in cybercrime investigations or a related area. Salary/Rate: You know the salary range you are looking for, so let's talk after you fill out the application. Note: No 3rd party vendors or candidates US Citizenship Required Active DHS Suitability nice to have

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 ********************