Data scientist jobs in The Woodlands, TX

ABOUT OUR CLIENT Our Client is a leading private equity firm with a portfolio of upstream gas production companies. By combining petroleum engineering expertise with advanced data analytics, artificial intelligence (AI), and machine learning (ML), Our Client is driving the digital transformation of upstream operations. With a diverse set of assets and a strong focus on innovation, this role provides the opportunity to shape the future of gas production and forecasting through cutting-edge technology. ABOUT THE ROLE The Petroleum Data Engineer will play a critical role in leveraging data to solve complex engineering challenges, optimize production, and drive operational efficiency across portfolio companies. This individual will build innovative data products, develop and deploy AI/ML models, automate workflows, and collaborate with engineering teams to unlock new insights. The role is ideal for a professional passionate about merging petroleum engineering expertise with modern data science to deliver measurable business impact. RESPONSIBILITIES Develop, optimize, and maintain data pipelines to automate upstream gas production and forecasting workflows Implement scalable data solutions to support monitoring, reservoir management, and efficiency initiatives Integrate structured and unstructured data from sensors, logs, and well data into production systems Design and deploy AI/ML models for production forecasting, reservoir simulation, and failure prediction Analyze historical and real-time production data to identify trends and optimization opportunities Collaborate with domain experts to align AI/ML models with engineering principles and field use cases Build and deploy data products in partnership with digital and engineering teams across portfolio companies Serve as a technical advisor to portfolio companies on data analytics and digital transformation initiatives Develop user-friendly dashboards and interfaces for data visualization and stakeholder engagement Ensure data quality, accuracy, and consistency across all pipelines and products Implement governance policies to secure sensitive production data and meet industry regulations Stay current with emerging technologies in petroleum data analytics, AI, and ML to drive innovation QUALIFICATIONS Bachelor's, Master's, or PhD in Petroleum Engineering, Data Science, Computer Science, or related field Five or more years of experience in upstream oil and gas, with a focus on gas production and forecasting Proven track record applying AI and ML to solve petroleum engineering challenges Proficiency in Python, R, or similar programming languages for data analytics and ML Hands-on experience with frameworks such as TensorFlow, PyTorch, or scikit-learn Strong understanding of upstream workflows, including reservoir simulation and optimization Experience with cloud platforms such as Azure, AWS, or Google Cloud, and tools like Databricks or Synapse Ability to build dashboards and visualizations using Power BI, Spotfire, or similar platforms PREFERRED QUALIFICATIONS Knowledge of digital oilfield technologies, IoT integration, and real-time data processing Experience with data governance frameworks and tools such as Microsoft Purview Familiarity with industry datasets and platforms including Enverus or IHS SOFT SKILLS Strong problem-solving abilities and innovative mindset Excellent communication skills, with the ability to explain technical concepts to non-technical stakeholders Collaborative approach to working across diverse teams and organizations WHAT YOU WILL ACHIEVE Deliver data-driven solutions that optimize gas production and forecasting across portfolio companies Enable portfolio companies to adopt AI/ML and advanced analytics as a competitive advantage Contribute to the digital transformation of upstream operations, shaping the future of the energy industry

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

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.

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

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!

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.

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

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

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.

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

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

Our client is currently seeking a Data Scientist to join their team in Bangalore, India. The Data Scientist will be supporting automation projects utilizing large data sets to find opportunities for product and process optimization. They will work with stakeholders across the finance organization to identify opportunities to leverage company data to drive business solutions. Daily they will analyze data to create custom data models and algorithms to assess the effectiveness and accuracy of data sources and data gathering techniques. They will use predictive modeling to increase and optimize customer experience, revenue generation, ad targeting, and other business outcomes. They will be responsible for developing processes and tolls to monitor & analyze model performance and data accuracy. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to ********************.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: **************************************************** Skills and Requirements 5+ years of experience as a Data Scientist Experience with Databricks, Python, and Power BI to manipulate data and draw insights from large data sets Understanding of the relationship between multiple data sets and how to build stories within Experience creating & using advanced machine learning algorithms & statistics (simulation, scenario analysis, modeling, etc.) Experience visualizing & presenting data for stakeholders using Power BI Experience with SQL and database management Bachelors degree Finance acumen/understanding of financial data

Job Description The Data Scientist role at its core links business strategy to the data. He/she will transform structured or unstructured data into actionable information and predictive models to make a big impact across the organization. This individual will break down the hairiest of problems by applying the full data science toolkit and provide insights to stakeholders across the organization to change minds and hearts. He/she will keep the customer front of mind in all of the work and optimize the customer experience, which will translate to creating long-term business value. As a pioneering Data Scientist at Daikin, he/she will influence the cultural change around how we use, talk about, and ultimately value our data assets, as part of a broader Digital Transformation. Position Responsibilities may include; Gather, process, clean, enrich, and integrate structured and unstructured data to build advanced models to turn data into insights; creatively analyze data to understand drivers of historical business performance and build predictive models to inform future business strategies Deep understanding of our organization's data structure; look for ways to improve to enhance our ability to perform robust data analysis; create new data sets when there is little or no data available, to inform marketing analysis Engage with third-party data providers to strengthen and enrich data models as needed; inform purchase of net new data Deeply understand all sources of data across the enterprise, link to data strategy, and continually evolve ability to measure and track key data points to enable data-driven decisions Collect and provide quantitative and qualitative information to measure effectiveness of marketing activities and answer strategic business questions Analyze and discern campaign execution, targeting and optimization of marketing investment to deliver sales and operating profit across brands Utilize visualization solutions to improve timeliness of data delivery and provide better visibility to decision makers to help them monitor, measure, or predict how the company is performing Perform marketing research & analysis to inform customer targeting & segmentation, in addition to longitudinal tracking of Customer Lifetime Value across the enterprise Assist with internal assessments of workflow processes to identify inefficiencies, especially those where Marketing is involved, and propose more efficient processes and procedures via process automation leveraging tech platforms Assist with maintenance and management of Marketing SQL database and Snowflake cloud data warehouse Provide data science support and ad hoc analysis to enterprise leadership as needed Nature and Scope: Applies advanced knowledge of job area typically obtained through advanced education and work experience Manages projects and processes while working independently and with limited supervision Coaches and reviews the work of lower-level professionals Problems faced are difficult and sometimes complex; takes a new perspective on existing solutions Knowledge and Skills: Mastery of analytical skills with attention to detail; mastery of statistical analysis, machine learning process, computer science principles, and basic programming principles Strong data storytelling ability - ability to produce actionable information/insights, not just data crunching Very strong communication skills, both verbally and written, capable of communicating with people of many different levels of an organization Experienced with experimentation and testing of Minimum Viable Products to determine if proposed business models / solutions scale up Proficient in MS Office especially Excel; ability to translate data insights into PowerPoint presentations Proficient in relational databases with strong experience in SQL - Microsoft SQL Server, Oracle, Postgres Proficient with A/B testing and data science techniques to build and implement predictive models Proficient with visualization tools such as Tableau, Qlik, or Microsoft Power BI (or similar applications) Proficient with Python, R, Alteryx or other analytics platforms a plus (or similar applications) Eager to make a big impact at a large company - you show up for work and get things done Natural ability and desire to work on a team - goes the extra mile when needed; ability to work independently too Ability to grasp complex concepts and systems quickly Ability to manage multiple projects and shift direction quickly Intellectual curiosity and strong passion for using data to solve problems creatively Experience: 5+ years of work experience in a Marketing / Consulting / Business Analyst / Data Science role Mastery solving complex business problems involving a heavy amount of analytics / data science Marketing-based experience (either D2C or B2B performance marketing) HVAC industry experience preferred, but not required Education: Bachelor's degree (required) in Marketing / Business / Engineering / Statistics / Mathematics / Economics / Computer Science; or other related degree with strong quantitative emphasis Master's degree (required) in Data Science / Business Administration / Marketing People Management: No Physical Requirements / Working Environment; Must be able to perform essential responsibilities with or without reasonable accommodations. Reports to: Manager, Data Science & Marketing Analytics

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

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

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