Senior data scientist jobs in Galveston, TX

********* 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.

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.

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

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.

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!

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.

Our client is seeking an experienced Data Engineer (5+ years) to join their Big Data and Advanced Analytics team. In this role, you'll collaborate closely with the Data Science team and various business units to tackle real-world challenges in the oil and gas midstream sector using machine learning, AI, and data-driven solutions. You'll also play a key role in shaping and advancing the organization's data engineering practices. Job Description Design, build, test, and maintain scalable data pipelines Independently handle analytics projects across multiple business functions Automate manual data processes for efficiency and scalability Develop data-intensive applications and APIs Create algorithms that turn raw data into actionable insights Deploy and operationalize machine learning and mathematical models Support data analysts and data scientists by streamlining data processing and model deployment Ensure data accuracy and consistency through quality checks Skills Required 5+ years of professional IT experience, ideally in network security engineering Strong experience with: Python (Pandas, NumPy, Pytest, Scikit-Learn) SQL Apache Airflow Kubernetes CI/CD pipelines Git version control Test-Driven Development (TDD) API development Familiarity with machine learning concepts and applications Education/Certifications High School Diploma or GED GAS Global Services LLC is an Equal Opportunity Employer. Employment Decision are made without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity or any other factors protected by applicable federal, state or local laws. JOB-10045560

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.

Department: IT - BI Finance/HCM/Ops Contract Months:12 Salary Range: $92,540.00 - $152,691.00 Academic Year: 25-26 The Senior Data Scientist - Strategic Data Intelligence leads advanced analytics, modeling, and predictive insights for Houston ISD's enterprise systems. This role focuses on data from Finance, Budgeting, Procurement, HR, and other ERP domains. The Senior Data Scientist works across departments to develop models that inform operational decision-making, forecast resource needs, and identify efficiency opportunities. The role plays a key part in ensuring HISD leverages Microsoft Fabric and Power BI to build intelligent, automated data tools that support a modern, cloud-based ERP landscape. MAJOR DUTIES & RESPONSIBILITIES 1. Build and maintain statistical and machine learning models using data from enterprise systems. 2. Partner with Finance, HR, Procurement, and Budgeting teams to understand strategic data needs. 3. Develop forecasts, classification models, or cluster analyses to optimize operations. 4. Create executive dashboards, simulations, and decision-support tools using Power BI and Microsoft Fabric. 5 Lead efforts to clean, normalize, and combine data from Oracle Fusion, legacy SAP, and other platforms. MAJOR DUTIES & RESPONSIBILITIES CONTINUED 6. Publish clear documentation and visual explanations of findings to both technical and non-technical audiences. 7. Collaborate with data engineers and architects to ensure models are reproducible and scalable. 8. Evaluate external datasets and economic indicators to enhance district forecasting. 9. Mentor other analysts and data professionals within the department. 10. Perform other job-related duties as assigned. EDUCATION Master's degree in data science, statistics, applied mathematics, or related quantitative field required. Ph.D. preferred. * Applicants who do not meet these education qualifications may be considered if they have a unique combination of education and work experiences that indicate potential for success in this role. WORK EXPERIENCE Minimum of 6 years in data science, analytics, or quantitative research. Experience with ERP or operational systems in education, government, or large enterprises preferred. SKILL AND/OR REQUIRED LICENSING/CERTIFICATION * Advanced experience with Python, R, or other statistical programming languages * Strong SQL and data modeling skills * Experience using Power BI and Microsoft Fabric for data analysis * Knowledge of ERP data structures (finance, HR, procurement) * Strong communication and data storytelling abilities * Preferred certifications: Microsoft Certified: Data Scientist Associate, Azure Data Scientist Associate LEADERSHIP RESPONSIBILITIES Serves as a senior contributor and thought leader within the Strategic Data Intelligence team. May lead projects or mentor junior analysts. WORK COMPLEXITY/INDEPENDENT JUDGMENT Applies independent judgment to solve complex, ambiguous problems. Chooses modeling approaches, variables, and algorithms based on context and stakeholder needs. BUDGET AUTHORITY May provide input on software, tools, or external data subscriptions needed to support modeling. PROBLEM SOLVING Translates large-scale, messy data into actionable insights and predictive tools. Identifies gaps and inefficiencies in data collection or usage. IMPACT OF DECISIONS Models and forecasts directly influence staffing, budgeting, procurement, and other enterprise decisions across HISD. COMMUNICATION/INTERACTIONS Presents models, insights, and scenarios to senior district leadership, department heads, and peer analysts. CUSTOMER RELATIONSHIPS Provides expert-level support to business units seeking to improve operations using predictive and statistical tools. WORKING/ENVIRONMENTAL CONDITIONS Office or hybrid setting. Extended screen time and data review required. May work long hours during major forecasting periods. Houston Independent School District is an equal opportunity employer.

Embark on a transformative journey with Cognite, a global SaaS forerunner in leveraging AI and data to unravel complex business challenges through our cutting-edge offerings including Cognite Atlas AI, an industrial agent workbench, and the Cognite Data Fusion (CDF) platform. We were awarded the 2022 Technology Innovation Leader for Global Digital Industrial Platforms & Cognite was recognized as 2024 Microsoft Energy and Resources Partner of the Year. In the realm of industrial digital transformation, we stand at the forefront, reshaping the future of Oil & Gas, Chemicals, Pharma and other Manufacturing and Energy sectors. Join us in this venture where AI and data meet ingenuity, and together, we forge the path to a smarter, more connected industrial future. Learn more about Cognite here Cognite Product Tour 2025 Cognite Product Tour 2024 Cognite Product Tour 2023 Data Contextualization Masterclass 2023 Our values Impact: Cogniters strive to make an impact in all that they do. We are result-oriented, always asking ourselves. Ownership: Cogniters embrace a culture of ownership. We go beyond our comfort zones to contribute to the greater good, fostering inclusivity and sharing responsibilities for challenges and success. Relentless: Cogniters are relentless in their pursuit of innovation. We are determined and deliverable (never ruthless or reckless), facing challenges head-on and viewing setbacks as opportunities for growth. The Data Science team at Cognite plays a crucial role in building data-driven solutions that empower our clients to make impactful business decisions. As a Senior Data Scientist at Cognite, you will work on challenging data problems with leaders in the industry. You will be a part of cross-functional teams that include data engineers, solution architects, and project managers. Together, your focus will be on configuring, deploying, and operationalizing digital solutions in sectors such as Oil and Gas, Power & Utilities, and Manufacturing. Additionally, you will engage with clients and Subject Matter Experts (SMEs) to understand their desired outcomes, lead discovery workshops, and provide insights on potential strategies and obstacles, ensuring the technical solution aligns with industrial reality. The Data Science team is a part of the AMER delivery team in our Global Delivery organization. Global Delivery is truly global, with offices in Houston & Phoenix (USA), Tokyo (Japan), Oslo (Norway), and Bengaluru (India). We are a good mix of Project Managers, Senior Data Scientists, Data Engineers, and Solution Architects with deep domain expertise. We are responsible for delivering successful projects that are flexible and scalable, and foster adoption of our product. In sum, we derive valuable insights from previously hidden data, enabling workers and leaders to transform how heavy asset industries operate to become more efficient and sustainable. What You'll Do * As a Senior Data Scientist you are responsible for the following, but not limited to: * Develop and deploy scalable solutions for customer use cases from Oil and Gas, Manufacturing, and Power & Utilities industries using Cognite's core capabilities. * Participate in intensive use case generation workshops with Subject Matter Experts (SMEs) to understand the problem, industry domain knowledge, and how it maps to the data. * Perform data cleansing and exploratory data analysis. * Implement physical models / machine learning models in Python and deploy to our model hosting environment. * Design and develop domain-specific information and data models. * Apply GenAI techniques to enhance data-driven decision-making in customer use cases. * Develop robust front-end User Interfaces (UIs) and dashboards using Streamlit, Grafana, Power BI, Plotly or Dash. Experience with React for bespoke UI development is a plus. * Leverage strong understanding of solution architecture to ensure deployed solutions are flexible, scalable, and fully integrated into the client's industrial landscape. * Utilize and contribute to solution templates and best practices within the Data Science team. * Mentoring and coaching junior team members is an important part of being a Senior at Cognite. * Collaborate with data engineers, project managers, and solution architects on project deliveries to enable our customers to achieve the full potential of our industrial dataops platform. * Support customers and partners in conducting data science tasks with Cognite products. Who You Are * Bachelor/Master of Science in a quantitative field or mechanical, systems, electrical, or industrial engineering. * 5+ years of full-time work experience as a Senior data scientist (preferably within related industry), or Senior data scientist with domain expertise in Oil and Gas or Maintenance or Manufacturing. * Proficient experience with Python and SQL. Experience with Python in a production setting is a plus. * Experience with machine learning methods and techniques, statistics and/or optimization as well as physics based modeling. * Experience with Git. * Experience working customer-faced, with external customers. * Front-end development experience with frameworks such as React or native knowledge of UI platforms like Streamlit/Dash is highly desired. * Understanding of solution architecture, system design, and deployment best practices in a cloud environment. * Experience with managed cloud services such as GCP, Azure or AWS is a plus. * Strong domain knowledge or a good understanding of Industry and Asset Performance Management-covering areas like production optimization-is a big plus. (As key CDF advisors, we want our Senior Data Scientist to have a good understanding of our customer data, and assist them in understanding how CDF can help solve their problems related to production optimization). * Enjoy working in cross-functional teams. * Able to deliver independently, coach and mentor others internally. * Enjoy challenges and dare to set ambitious goals that drive innovation. * Humility to ask for help and enjoy sharing knowledge with others. Why choose Cognite? * Join us in making a real and lasting impact in one of the most exciting and fastest-growing new software companies in the world. * We have repeatedly demonstrated that digital transformation, when anchored on strong DataOps, drives business value and sustainability for clients and allows front-line workers, as well as domain experts, to make better decisions every single day. * Cognite Earns 2023 Microsoft Partner of the Year Award; Recognized as a Global Leader in Energy & Resources and Industrials & Manufacturing * Frost & Sullivan named Cognite a Technology Innovation Leader! * Built In 2024 Best Places to Work in Austin, TX and Houston, TX * Cognite Recognized as 2024 Microsoft Energy and Resources Partner of the Year * Most recently Cognite Data Fusion Achieved Industry First DNV Compliance for Digital Twins A snapshot of our many perks and benefits as a Cogniter * Competitive compensation * 401(k) with employer matching * Competitive health, dental, vision & disability coverages for employees and all dependents * Unlimited PTO * Paid Parental Leave Program * Employee Referral Program * Join a team of 60+ different nationalities with Diversity, Equality and Inclusion (DEI) in focus . * A highly modern and fun working environment with sublime culture across the organization, follow us on Instagram @cognitedata to know more * Opportunity to work with and learn from some of the best people on some of the most ambitious projects found anywhere, across industries * Join our HUB ️ to be part of the conversation directly with Cogniters and our partners. * Paid mobile phone and WiFI All candidates must be legally authorized to work in the United States without the need for current or future company sponsorship for employment visa status. Equal Opportunity Cognite is committed to creating a diverse and inclusive environment at work and is proud to be an equal opportunity employer. All qualified applicants will receive the same level of consideration for employment; everyone we hire will receive the same level of consideration for training, compensation, and promotion. We ask for gender as part of our application because we want to ensure equal assessment in the recruitment process. Your answer will help us reach this commitment! However, the question about gender is optional and your choice not to answer will not affect the assessment of your application in any way. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Empower Your Future: At MetOx International, we're pioneering the next era of energy security and abundance through breakthrough superconducting technology. As a Senior Data Scientist, you'll join a dynamic team committed to strengthening the world's energy systems to make them more resilient, efficient, and reliable. Based at our global headquarters in Houston, TX, the Senior Data Scientist will lead advanced analytics, modeling, and machine learning efforts across our manufacturing operations. In this role, you will partner closely with R&D, process engineering, quality, and operations to translate complex process challenges into data-driven insights that improve yield, quality, and scalability. This is a highly technical, hands-on role for someone who thrives at the intersection of process engineering, applied mathematics, and industrial data science, and who is excited to drive measurable impact in advanced materials manufacturing. Key Responsibilities Process Analytics & Optimization Develops and deploys statistical models for process characterization, optimization, and quality control in superconductor manufacturing. Designs and executes design of experiments (DOE) to identify critical process parameters and optimize production outcomes. Implements statistical process control (SPC) methodologies including multivariate control charts and process capability analysis. Conducts root cause analysis using advanced statistical techniques combined with process engineering knowledge. Advanced Modeling & Machine Learning Builds physics-informed models that combine first-principles engineering with machine learning approaches. Develops predictive models for yield optimization, defect detection, and predictive maintenance. Applies time-series analysis and forecasting for process monitoring and anomaly detection. Implements computer vision and machine learning solutions for automated quality inspection. Mathematical Modeling & Simulation Applies advanced mathematical techniques including optimization theory, differential equations, and numerical methods to solve complex manufacturing challenges. Develops digital twins and process simulation models for scenario analysis and process improvement. Performs multivariate statistical analysis to understand complex interactions in manufacturing processes. Builds decision support tools using mathematical optimization for production planning and resource allocation. ⠀Data Infrastructure & Pipeline Development Designs and implements scalable data pipelines for real-time process monitoring across manufacturing operations. Integrates data from multiple sources including SCADA systems, MES platforms, databases, and sensor networks. Develops automated reporting systems for KPI tracking, process drift detection, and quality metrics. Establishes best practices for data governance, version control, and reproducible research. Technical Leadership & Collaboration Leads cross-functional data science projects involving R&D, process engineering, quality, and operations teams. Mentors junior data scientists and engineers on statistical methods, machine learning, and best practices. Translates complex process engineering challenges into tractable data science problems. Communicates analytical findings and recommendations to technical and executive stakeholders. Drives adoption of data-driven decision-making and advanced analytics across the organization. Other duties as assigned Minimum Qualifications: Bachelor's degree in Chemical Engineering, Materials Science, Applied Mathematics, Statistics, Data Science, or related technical field. 4 years of professional experience in data science or analytics within manufacturing, process engineering, or industrial R&D environments. Demonstrated experience in statistical process control, design of experiments, and process optimization. Preferred Qualifications: Master's or PhD in Chemical Engineering, Materials Science, Applied Mathematics, Statistics, or related field. Experience in process-intensive industries (semiconductor, chemical, pharmaceutical, or advanced materials manufacturing). Six Sigma Black Belt or equivalent process improvement certification. Experience with superconductor manufacturing, electrochemistry, thin-film deposition, or related materials processes. Publication record in process engineering, applied statistics, or machine learning. Experience with industrial automation systems (SCADA, MES, OPC, MQTT). Knowledge, Skills, & Abilities: Process Engineering & Domain Knowledge Deep understanding of manufacturing processes, unit operations, and process dynamics. Expertise in statistical process control (SPC), process capability analysis (Cp, Cpk), and control chart theory. Proficiency with design of experiments including factorial designs, response surface methodology, and Taguchi methods. Knowledge of quality management systems and continuous improvement methodologies. Strong foundation in mathematical modeling and advanced statistical methods Expert knowledge of multivariate statistics, time-series analysis, hypothesis testing, and Bayesian inference. Strong foundation in linear algebra, calculus, differential equations, and optimization theory. Experience with dimensionality reduction techniques (PCA, PLS, factor analysis). Understanding of numerical methods and computational algorithms. Machine Learning & AI Advanced proficiency in machine learning techniques including regression, classification, ensemble methods, and neural networks. Experience with computer vision and deep learning frameworks (TensorFlow, PyTorch, YOLO, etc.). Knowledge of model validation, cross-validation, and hyperparameter optimization. Familiarity with MLOps practices for model deployment and monitoring. Technical Programming & Tools Expert-level programming in Python (NumPy, SciPy, Pandas, Scikit-learn, Matplotlib, Plotly). Proficiency with statistical analysis software (Minitab, JMP, or equivalent). Advanced SQL skills for complex data extraction and manipulation from manufacturing databases. Experience with version control (Git), containerization (Docker), and CI/CD practices. Familiarity with data visualization platforms (Grafana, Tableau, Power BI, Metabase). Soft Skills & Leadership Exceptional analytical and problem-solving abilities with attention to detail. Strong communication skills with ability to explain complex mathematical and statistical concepts to diverse audiences. Proven ability to lead projects and mentor team members. Self-motivated with ability to work independently and manage multiple priorities. Collaborative mindset with experience working across engineering, operations, and business functions. Strategic thinking with ability to connect data insights to business objectives. Physical Demands: This position requires sitting at a desk and viewing a computer screen for extended periods while working or performing other office tasks. Ability to move around the office, including occasional standing, walking, and bending to retrieve documents, attend meetings, or use office equipment. Some light lifting may be required, up to 20 lbs. MetOx is proud to offer competitive benefits including: Health, dental, and vision available on the first day of employment 401(k) match Paid parental leave & adoption assistance Educational reimbursement And more! We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.

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.

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

**Remote Opportunity** Based in Houston, Texas, with offices in London and New York, SynMax is a pioneering data intelligence company specializing in maritime and energy intelligence. By integrating advanced satellite imagery and AI, SynMax delivers unparalleled insights into maritime operations, oil and gas development, coal inventory, and LNG flows, enabling businesses and organizations to make data-driven decisions with precision and confidence. Job Description:We are seeking a talented Data Scientist with expertise in algorithm development, Google Cloud Platform, geospatial data analysis, and relational databases to join our team. As a Data Scientist at SynMax, you will play a leading role in developing solutions for industry disrupting analytics software. The ideal candidate will have experience with data fusion. To succeed in this role you will be highly motivated and adaptable to changing needs as our company grows. Responsibilities Collaborate with analysts and domain experts to understand business requirements and translate them into technical product solutions. Design and implement probabilistic and deterministic algorithms for information extraction and fusion from a variety of remote sensing and proprietary data sources. Perform exploratory data analysis for problem definition and refinement. Develop and test candidate algorithms to demonstrate tradeoffs for final selection. Assemble and clean training and test datasets. Perform model training. Iterate to meet model performance requirements. Develop and maintain Python-based applications for processing volatile live data streams on Google Cloud Platform. Work closely with relational databases and execute complex queries to extract actionable insights from geospatial data. Optimize application performance and scalability to ensure flawless operation under heavy load conditions. Implement best practices for code quality, testing, and deployment automation in a continuous integration and deployment (CI/CD) environment. Stay updated on emerging technologies and industry trends related to real-time data processing, algorithms, machine learning, geospatial analysis, and cloud computing. Qualifications PhD or MS degree in Computer Science (preferred), or STEM field. Ability to apply machine learning, statistics, and optimization principles to problem solving. Experience in linear programming and graph based methods are a plus. 2 years minimum experience in a Data Scientist role. Hands-on experience building Google Cloud Platform highly scalable data processing pipelines for volatile live data streams. Ability to take ownership of project tasks through to completion, producing positive outcomes despite unforeseen complexity. Knowledge of geospatial data formats (e.g., GeoJSON, Shapefiles), libraries (e.g., Geopandas, GDAL, Fiona, Shapely) and spatial database query syntax (e.g., PostGIS) Proficient in image processing, algorithm and machine learning libraries (SciPy, Pytorch, Tensorflow, Scikit-Image, Scikit-Learn, OpenCV) The ability to work effectively in a team environment with remotely located staff in different time zones, demonstrating strong communication and coordination skills. What We Offer Competitive salary and benefits package. Opportunities for professional development and career growth. A dynamic and collaborative work environment where innovation is encouraged. Access to the latest tools and technologies. Equal Opportunity Statement:SynMax is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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

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