Senior data scientist jobs in Baytown, TX

COMPANY The Company specializes in digital enablement and transformation using industry-leading process mining, data management and automation platforms. They help Fortune 500 companies become more process-efficient and improve their end-customer experience through the use of RPA, AI & ML powered solutions. The company has been growing at an accelerated pace and is looking to add experienced folks to their core technology team. POSITION SUMMARY we are looking for a Senior Data Scientist to help drive actionable insights using artificial intelligence and machine learning algorithms. The candidate should conduct and manage analysis and modelling in the areas of machine learning, neural networks, robotics etc. KEY RESPONSIBILITIES Work with business partners within one business process to align technology solutions with business strategies. Ability to translate business questions into analytical problems and recommend solutions using statistical modelling, text mining, machine learning, artificial intelligence techniques Utilize technologies to collect, clean and analyze data from multiple systems and mine insights Conceptualize, design, and deliver high quality solutions and insightful analysis using algorithms like Neutral Networks, Genetic Algorithm, Deep Learning, Reinforcement Learning and effectively communicates information Contribute to multiple projects and collaborate with other team members for timely and successful delivery. REQUIRED EXPERIENCE, SKILLS & EDUCATION 9+ years of relevant experience conducting text mining, NLP, machine learning, deep learning, artificial intelligence techniques-based models Tool Expertise - Python, R, SQL, SAS Good To Have Experience in working on Big data, Cloud, Hadoop, Spark, End to end deployment Strong background in developing and supporting very large-scale analytical solutions Ability to be an independent contributor to solve complex data-analytics problems Industry experience in High-Tech, Manufacturing, Retail, Pharma Master's degree in statistics, mathematics, computer science, business analytics

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.

Benefits: 401(k) Competitive salary Dental insurance Health insurance Paid time off A Lead Data Scientist is responsible for managing data science projects, leading a team, and utilizing advanced analytics to drive business decisions and product improvements.Key Responsibilities Team Management: Lead and mentor a team of data scientists, machine learning engineers, and big data specialists to foster professional growth and collaboration. Project Planning: Oversee the planning and execution of data science projects, ensuring alignment with organizational goals and objectives. Model Development: Build and optimize analytical models using machine learning, natural language processing, and statistical techniques to derive insights from large datasets. Data Analysis: Analyze various data sources, including procurement, supply chain, and healthcare data, to inform business strategies and product development. Problem Solving: Identify and address data development challenges, proposing innovative solutions to enhance data utilization across the organization. Methodology Development: Lead the development and maintenance of methodologies that support product offerings, including statistical modeling and time-series analysis. Stakeholder Collaboration: Work closely with business leaders and other departments to communicate analytical findings and drive data-driven decision-making. Required Skills and Qualifications Educational Background: Typically requires a Master's or Ph.D. in Statistics, Computer Science, Mathematics, or a related field. Technical Expertise: Proficiency in data manipulation, visualization, and machine learning techniques, with experience in programming languages such as Python, R, or SQL. Analytical Skills: Strong problem-solving abilities and a knack for statistical analysis to interpret complex data sets effectively. Leadership Skills: Experience in managing teams and projects, with the ability to mentor junior data scientists and foster a collaborative environment. Communication Skills: Excellent verbal and written communication skills to convey complex analytical concepts to non-technical stakeholders. Salary Expectations $125,000 - $140,000 Compensation: $125,000.00 - $140,000.00 per year PROVIDING QUALITY STAFFING AND CONSULTING SINCE 2011 Based out of San Antonio, Tex as, our minority women-owned company specializes in all staffing and consulting needs. Whether you're trying to hire a pharmacist, a respiratory therapist, or skilled and non-skilled laborer, we will staff your company with the best candidate. We bring extensive experience and professionalism and we will personalize our assistance to your needs and concerns. Most of our contracts are with the Army and Air Force as Sub-Contractors. Our staff has a quick turn around and have been able to fill positions within 48 hours with short notice, we have filled hard to fill locations and jobs, and managed over 16 contracts with over 70 employees at a time. Managed call-ins at 24/7 hospitals and ensured shifts were filled, and managed PRNs with notice of less than 24 hours. Also, provided temp laborers for next day jobs. Our consulting division provides contracting assistance, program managing, application assistance, certification assistance and proposal writing. We are very knowledgeable in a variety of areas and are eager to assist your company's prosperity.

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

At IMO Health, a core team of software developers, data scientists, and domain experts combine computer science, healthcare, and life sciences expertise to help professionals access high-quality health information quickly and easily. We are seeking a Staff Data Scientist with deep expertise in statistical modeling, meta-analysis methodologies, AI/LLM technologies, and real-world evidence (RWE) generation to help design and develop innovative tools that empower clients to conduct advanced evidence synthesis and analysis. This role sits at the intersection of science, technology, and client delivery - translating complex analytical workflows into intelligent, scalable software solutions. You will collaborate with cross-functional teams to design, build, and optimize AI-enabled tools for meta-analysis. The ideal candidate will bring strong scientific understanding, product-thinking mindset, and experience implementing cloud-based AI infrastructure, scalable ML pipelines, and MLOps best practices to deliver robust, client-facing solutions in the life sciences domain. Join our growing Data Science & Analytics department as a Staff Data Scientist to drive AI-powered innovation in healthcare and life sciences! WHAT YOU'LL DO: Design and develop AI-driven software tools that enable clients to perform meta-analysis, systematic reviews, and real-world evidence (RWE) generation efficiently and accurately. Translate complex statistical and meta-analytic workflows into scalable, automated product features and user-facing applications. Collaborate with cross-functional teams to ensure scientific rigor, methodological validity, and usability of developed solutions. Leverage LLMs, prompt engineering, and information extraction techniques to automate literature review, data curation, and evidence synthesis from clinical and real-world data sources. Build and maintain scalable data and AI pipelines, integrating diverse data sources including structured, unstructured, and real-world datasets. Ensure compliance with data privacy, security, and regulatory standards across all data handling and model deployment activities. Implement modern software engineering and MLOps best practices, including CI/CD, testing, monitoring, and version control, to support scalable and reliable deployments. Evaluate emerging AI/ML and statistical technologies, drive proof-of-concept initiatives, and shape the technical roadmap for evidence-generation tools. Interpret and communicate insights effectively to both technical and non-technical stakeholders through visualizations, reports, and presentations. Mentor and support team members, fostering skill development in NLP, LLMs, and statistical modeling for healthcare applications. Champion a culture of scientific and technical excellence, continuous learning, and innovation in applying AI to healthcare and life sciences challenges. WHAT YOU'LL NEED: PhD preferred (or Master's with 8+ years of experience) in Biostatistics, Bioinformatics, Computer Science, Health Informatics, or a related field. Deep understanding of statistical modeling, meta-analysis methodology, and evidence synthesis techniques relevant to post-market and real-world evidence (RWE) applications. Strong background in NLP, and AI principles, with a focus on LLMs, prompt engineering, and information extraction from scientific text. Proficiency in Python and major ML/NLP frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, and scikit-learn. Demonstrated experience designing and deploying AI-driven analytical tools or platforms, including LLM-based workflows for literature mining, evidence synthesis, or clinical data interpretation. Familiarity with vector databases (e.g., Pinecone, PostgreSQL) and knowledge graph or semantic data modeling for organizing biomedical and clinical information. Strong grasp of experimental design, statistical inference, and validation methods to ensure scientific rigor in software outputs. Experience in biomedical or healthcare data analysis, including integration of real-world data sources such as literatures, EHR, claims, or registry data. Understanding of data privacy, ethics, and regulatory requirements in healthcare (e.g., HIPAA). Proven ability to collaborate cross-functionally with engineers, scientists, domain experts and clients. Excellent communication, documentation, and presentation skills; demonstrated experience mentoring colleagues and contributing to scientific publications or conference presentations in the life sciences domain. Curious, innovative, and solution-oriented mindset with a passion for building tools that advance evidence generation and decision-making in life sciences.

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

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

Lead Data Scientist The Lead Data Scientist is responsible for driving advanced analytics initiatives and leading complex data science projects across the organization. This role oversees the analysis of large, diverse, and unstructured datasets using advanced statistical and machine-learning methods to support data-driven decision-making. The Lead Data Scientist partners with cross-functional teams, mentors other data scientists, and provides strategic insights on high-impact business challenges. This position typically reports to a Data Science Manager. Minimum Qualifications Education Bachelor's degree in Science, Engineering, Computer Science, Mathematics, Statistics, or another STEM-related field (required) Master's degree in Data Science preferred Experience / Knowledge / Skills 7+ years of data science experience Experience in healthcare analytics, hospital operations, medical informatics, EHR data, or healthcare IT (preferred) Strong business analysis capabilities, including workflow analysis, modeling, and process evaluation Deep understanding of machine learning techniques (e.g., clustering, neural networks, decision trees) and their practical applications Advanced proficiency in statistical methods (regression, statistical testing, distribution properties, etc.) Strong experience communicating insights, gathering requirements, and storytelling with data Advanced knowledge of the data science life cycle, model development, and deployment Proficiency in programming languages commonly used in data science (e.g., Python, R) Strong SQL skills and experience with large, complex datasets Exceptional problem-solving, analytical reasoning, and decision-making abilities Ability to manage multiple projects independently in fast-paced environments Excellent written and verbal communication skills for technical and non-technical audiences Strong project management skills with a commitment to delivering high-quality work Ability to troubleshoot and resolve data quality issues Experience working with time-series forecasting, A/B testing, clustering, and other data science methods Ability to mentor junior team members and support broader data literacy initiatives Principal Accountabilities Lead and manage high-impact data science projects that support business strategy and operational improvements Provide technical leadership and mentorship to data science team members Develop advanced statistical models, predictive algorithms, and machine-learning solutions Conduct research and analysis on structured and unstructured datasets to uncover actionable insights Maintain, evaluate, and refine existing analytical models to ensure accuracy and relevance Communicate findings clearly and effectively to leadership and cross-functional teams Partner with internal stakeholders to identify data issues and optimize data processes for efficiency and scalability Support evaluation and selection of data science tools and vendors Contribute to building data science best practices, frameworks, and methodologies Promote continuous learning, development, and knowledge sharing within the team Uphold organizational standards related to quality, compliance, and operational excellence Participate in professional development, continuing education, and team-based initiatives Perform additional responsibilities as assigned For more details reach at ******************************. About Navitas Partners, LLC: It is a certified WBENC and one of the fastest-growing Technical / IT staffing firms in the US providing services to numerous clients. We offer the most competitive pay for every position. We understand this is a partnership. You will not be blindsided and your salary will be discussed upfront.

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

People are our passion and purpose. Come work where you are valued for who you are, not just for what you can do. Remote Core Solutions provides tailored outsourcing and recruiting solutions, connecting high-performing talent with companies across a wide range of industries from startups to large enterprises. We take pride in matching candidates with roles where they can grow, innovate, and make an impact. About Our Client: Our client is a nationally recognized healthcare system focused on innovation, technology, and data-driven decision-making. Their enterprise data and analytics team supports transformative work across patient care, operations, and strategic initiatives. As they continue to invest in AI and data science, were helping them hire a dynamic Lead Data Scientist to spearhead strategic analytics projects, machine learning models, and executive-level insights across the organization. This role will be in person, in Houston, TX. About the Role: The Lead Data Scientist will lead critical enterprise-wide data science initiatives, manage high priority projects, and provide mentorship to junior data scientists. The ideal candidate is a hands-on builder who thrives at the intersection of healthcare, machine learning, and executive-level strategy. You'll be responsible for designing advanced models, leading stakeholder communication, and driving data science maturity across the organization. Responsibilities: Lead the design, development, and implementation of predictive and prescriptive data science models using healthcare and EHR datasets. Build, maintain, and validate machine learning algorithms for structured and unstructured data. Translate complex findings into actionable insights and present them to senior leadership and C-level executives. Develop custom data pipelines and oversee large-scale data set construction. Mentor junior data scientists and support ongoing training within the department. Serve as project lead on cross-functional initiatives involving clinical, finance, and operations data. Partner with key stakeholders to identify high-impact opportunities for analytics across departments. Maintain and optimize existing models, monitor model drift, and validate performance over time. Actively participate in vendor evaluations and provide recommendations for new tools and platforms. Ensure best practices in documentation, version control, and reproducibility across projects. Must-Haves: Bachelors Degree in a STEM related field (Science, Engineering, Mathematics, or Computer Science) Master's preferred. 7+ years of hands-on data science experience. Proven project leadership experience and ability to drive results independently. Strong communication skills with experience presenting to C-level stakeholders. Extensive experience building custom datasets and applying ML techniques (e.g., neural networks, regression models, clustering, forecasting). Cogito experience is required. AWS Certification is mandatory. Advanced experience with statistical programming (Python, R, or similar), SQL, and data visualization tools. Healthcare or hospital data environment experience preferred (e.g., EHR, revenue cycle, or clinical data). Interview Process: Recruiter Interview / Screening Hiring Manager Interview Final Panel Interview

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

**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.

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

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

HP Inc. is seeking a Data Scientist / ML Engineer to build and deploy scalable machine learning solutions using large-scale device and customer data. This role combines advanced modeling, experimentation, and MLOps with strong data engineering and API integration skills. You will work across cloud platforms, big data systems, and cross-functional teams to drive monetization, personalization, and business intelligence. **Key Responsibilities** + Design, train, and deploy machine learning and deep learning models, including propensity models, recommendation engines, and customer behavior prediction systems. + Own the full ML lifecycle-from feature development through training, evaluation, deployment, and ongoing model monitoring using scalable MLOps pipelines. + Collaborate with data engineering and business teams to operationalize insights and ML models. + Design and maintain large-scale ETL/ELT data workflows and integrate structured/unstructured data. + Develop and integrate with REST and GraphQL APIs for data ingestion and ML-driven services. + Leverage Python, SQL, Databricks and Apache Spark for data exploration, mining, cleansing and transformation. + Conduct A/B testing, statistical analysis, and experimentation to improve engagement and business KPIs. + Implement secure coding practices and leverage Git, CI/CD, and automated testing. **Requirements** + Bachelor's or Master's in CS, Data Science, Engineering, Statistics, or related field. + 7-10 years in data science, ML engineering, or data engineering roles. + Proficiency in Python, SQL, ML frameworks, and distributed data processing (Spark, Databricks). + Experience with AWS and Azure. + Strong ETL/ELT skills and experience with large-scale datasets. + Experience with REST/GraphQL APIs and third-party API integration. + Strong understanding of Git, CI/CD, and production-grade ML systems. The pay range for this role is **$130,350** to **$200,750** USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience. **Benefits:** HP offers a comprehensive benefits package for this position, including: + Health insurance + Dental insurance + Vision insurance + Long term/short term disability insurance + Employee assistance program + Flexible spending account + Life insurance + Generous time off policies, including; + 4-12 weeks fully paid parental leave based on tenure + 11 paid holidays + Additional flexible paid vacation and sick leave (US benefits overview (********************************** ) The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Introduction In this role, you will join IBM Consulting via our world-class Associates Program for university hires. As an Associate Data Scientist at IBM Consulting, you will have the opportunity to work with a diverse range of clients worldwide. Our clients' technical and business needs are constantly evolving. We're hiring inspired, talented individuals who believe no problem is too big to solve. We focus on your professional development through ongoing learning, mentorship, development of technical skills, and continuous personal growth, all grounded in a culture of coaching and career advancement. If you see yourself as someone who never stops learning and who wants to unleash your potential, the IBM Consulting Associates Program is for you. A career in IBM Consulting is rooted in long-term relationships and close collaboration with clients across the globe. You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio, including Software and Red Hat. Curiosity and a constant quest for knowledge serve as the foundation for success in IBM Consulting. In your role, you'll be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions that result in ground-breaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experience. Your role and responsibilities As an Associate Data Scientist at IBM, you will work to solve business problems using leading-edge and open-source tools such as Python, R, and TensorFlow, combined with IBM tools and our AI application suites. You will prepare, analyze, and understand data to deliver insight, predict emerging trends, and provide recommendations to stakeholders. In your role, you may be responsible for: * Implementing and validating predictive and prescriptive models, creating and maintaining statistical models with a focus on big data and incorporating machine learning techniques in your projects * Writing programs to cleanse and integrate data in an efficient and reusable manner * Working in an Agile, collaborative environment, partnering with other data scientists, engineers, consultants, and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviors * Communicating with internal and external clients to understand and define business needs and appropriate modeling techniques to provide analytical solutions. * Evaluating modeling results and communicating the results to technical and non-technical audiences. These positions are anticipated to start in 2026. We have positions open in these locations: * Atlanta, GA * Austin, TX * Chicago, IL * Houston, TX * New York, NY Required education High School Diploma/GED Preferred education Bachelor's Degree Required technical and professional expertise * Strong fundamentals in Mathematics and Computer Science (algorithms) * You're proficient in least one of the statistical programming languages, such as R, Python, Scala, SAS, SPSS, or Matlab * You have a basic understanding of or experience with predictive/prescriptive modeling skills * You have strong technical and analytical abilities, a knack for driving impact and growth, and some experience with programming/scripting in a language such as Java or Python * You're great at solving problems by looking at things differently, debugging, troubleshooting, and designing and implementing solutions to complex technical issues * Willingness to travel up to 100% Preferred technical and professional experience * You thrive on teamwork and have excellent verbal and written communication skills. * You have a basic understanding of Cloud (AWS, Azure, etc.) * Familiarity with constructing usable data sets from multiple structured and unstructured data sources ABOUT BUSINESS UNIT IBM Consulting is IBM's consulting and global professional services business, with market leading capabilities in business and technology transformation. With deep expertise in many industries, we offer strategy, experience, technology, and operations services to many of the most innovative and valuable companies in the world. Our people are focused on accelerating our clients' businesses through the power of collaboration. We believe in the power of technology responsibly used to help people, partners and the planet. YOUR LIFE @ IBM In a world where technology never stands still, we understand that, dedication to our clients success, innovation that matters, and trust and personal responsibility in all our relationships, lives in what we do as IBMers as we strive to be the catalyst that makes the world work better. Being an IBMer means you'll be able to learn and develop yourself and your career, you'll be encouraged to be courageous and experiment everyday, all whilst having continuous trust and support in an environment where everyone can thrive whatever their personal or professional background. Our IBMers are growth minded, always staying curious, open to feedback and learning new information and skills to constantly transform themselves and our company. They are trusted to provide on-going feedback to help other IBMers grow, as well as collaborate with colleagues keeping in mind a team focused approach to include different perspectives to drive exceptional outcomes for our customers. The courage our IBMers have to make critical decisions everyday is essential to IBM becoming the catalyst for progress, always embracing challenges with resources they have to hand, a can-do attitude and always striving for an outcome focused approach within everything that they do. Are you ready to be an IBMer? ABOUT IBM IBM's greatest invention is the IBMer. We believe that through the application of intelligence, reason and science, we can improve business, society and the human condition, bringing the power of an open hybrid cloud and AI strategy to life for our clients and partners around the world. Restlessly reinventing since 1911, we are not only one of the largest corporate organizations in the world, we're also one of the biggest technology and consulting employers, with many of the Fortune 500 companies relying on the IBM Cloud to run their business. At IBM, we pride ourselves on being an early adopter of artificial intelligence, quantum computing and blockchain. Now it's time for you to join us on our journey to being a responsible technology innovator and a force for good in the world. IBM is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, genetics, pregnancy, disability, neurodivergence, age, or other characteristics protected by the applicable law. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status. OTHER RELEVANT JOB DETAILS IBM offers a competitive and comprehensive benefits program. Eligible employees may have access to: * Healthcare benefits including medical & prescription drug coverage, dental, vision, and mental health & well being * Financial programs such as 401(k), cash balance pension plan, the IBM Employee Stock Purchase Plan, financial counseling, life insurance, short & long- term disability coverage, and opportunities for performance based salary incentive programs * Generous paid time off including 12 holidays, minimum 56 hours sick time, 120 hours vacation, 12 weeks parental bonding leave in accordance with IBM Policy, and other Paid Care Leave programs. IBM also offers paid family leave benefits to eligible employees where required by applicable law * Training and educational resources on our personalized, AI-driven learning platform where IBMers can grow skills and obtain industry-recognized certifications to achieve their career goals * Diverse and inclusive employee resource groups, giving & volunteer opportunities, and discounts on retail products, services & experiences We consider qualified applicants with criminal histories, consistent with applicable law. This position was posted on the date cited in the key job details section and is anticipated to remain posted for 21 days from this date or less if not needed to fill the role. IBM will not be providing visa sponsorship for this position now or in the future. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship. The compensation range and benefits for this position are based on a full-time schedule for a full calendar year. The salary will vary depending on your job-related skills, experience and location. Pay increment and frequency of pay will be in accordance with employment classification and applicable laws. For part time roles, your compensation and benefits will be adjusted to reflect your hours. Benefits may be pro-rated for those who start working during the calendar year.

At Stewart, we know that success begins with great people. As a Stewart employee, you'll be joining a company that was named a 2024-2025 Best Company to Work For by U.S. News & World Report, and a 2025 Top Workplace by USA Today. We are committed to helping you own, develop, and nurture your career. We invest in your career journey because we understand that as you grow, so does our company. And our priority is smart growth - by attaining the best people, investing in tools and resources that enable success, and creating a better home for all. You will be part of an inclusive work environment that reflects the customers we serve. You'll be empowered to use your unique experiences, passion and skills to help our company and the communities we serve constantly evolve and improve. Together, we can achieve our vision of becoming the premier title and real estate services company. Stewart is a global real estate services company, providing title insurance, settlement, underwriting, and lender services through our family of companies. To learn more about Stewart, visit stewart.com/about. More information can be found on stewart.com. Get title industry information and insights at stewart.com/insights. Follow Stewart on Facebook @StewartTitleCo, on Instagram @StewartTitleCo and on LinkedIn @StewartTitle Job Description Job Summary Design, build, and optimize data pipelines across both on-premises SQL Server environments , Azure cloud data services and MS Dynamics Dataverse. Job Responsibilities Design, develop, and maintain data pipelines to extract, transform, and load (ETL/ELT) data from multiple sources (on-prem and cloud) into analytical and operational systems. Provides data-based trends, recommendations and resolutions to the organization including through the optimization of monitoring and logging data pipelines Performs specialized assignments including the migration and integration of SQL Server data to Azure Data Lake, Azure SQL Database, MS D365 Dataverse, Synapse or Fabric. Interprets internal/external business environment Recommends best practices and implement data transformation and processing logic to optimize processes for performance and cost-efficiency using Azure-native tools. Using understanding of data modeling, normalization, and dimensional modeling concepts Impacts achievements of customer, operational, project or service objectives by utilizing skills in Python or PySpark for data transformation and automation. Communicates difficult concepts to team and departments to generate clarity and alignment on projects, initiatives, and various work products May lead functional projects with moderate risks and resource requirements Individual contributor working independently; may require guidance in highly complex situations Performs all other duties as assigned by management Education Bachelor's degree in relevant field preferred Experience Typically requires 5+ years of related work experience Strong experience in data movement, transformation, and processing of large-volume datasets. Proficiency in ETL/ELT frameworks, data orchestration, and automation. Hands-on experience with Azure Data Factory (ADF), Azure Synapse Analytics, Azure SQL, and Azure Data Lake Storage (ADLS Gen2) Knowledge of version control (Git) and CI/CD principles for data solutions. Strong expertise in Microsoft SQL Server (on-prem) performance tuning, stored procedures, and large-scale data processing Equal Employment Opportunity Employer Stewart is committed to ensuring that its online application process provides an equal employment opportunity to all job seekers, including individuals with disabilities. If you have a disability and need assistance or an accommodation in the application process, please contact us by email at *******************. Benefits Stewart offers eligible employees a competitive benefits package that includes, but is not limited to a variety of health and wellness insurance options and programs, paid time off, 401(k) with company match, employee stock purchase program, and employee discounts.

The Senior Data Engineer will play a critical role in building and scaling Crescent Energy's data platform to support analytics, reporting, and operational insights. This role requires deep expertise in Snowflake and cloud technologies (AWS) , with strong upstream oil & gas domain knowledge. The engineer will design and optimize data pipelines, enforce data quality and governance standards, and partner with business stakeholders to deliver reliable and scalable data solutions. Key Responsibilities: Data Architecture & Engineering Design, develop, and maintain data pipelines using Snowflake, AWS/Azure, and modern data engineering tools. Implement ETL/ELT processes to integrate data from diverse upstream systems (SCADA, production accounting, drilling, completions, etc.). Architect & develop scalable data models that support both operational reporting and advanced analytics use cases. Establish frameworks for data quality, validation, and lineage to ensure trust in enterprise data. Platform Development & Optimization Lead the build and optimization of Snowflake-based data warehouses, focusing on performance and cost efficiency. Design and implement cloud-native data solutions leveraging AWS/Azure services (e.g., S3, Lambda, Azure Data Factory, Databricks). Manage large-scale, time-series, and operational data processing workflows. Implement robust security, access management, and governance practices. Technical Leadership & Innovation Provide technical guidance and mentor junior team members. Evaluate and introduce new technologies and best practices to enhance data platform capabilities. Build reusable components, frameworks, and automation utilities to accelerate delivery. Support AI/ML initiatives by delivering production-ready, high-quality data pipelines. Business Partnership Partner with the stakeholders across all business units to capture and translate data requirements into technical solutions. Collaborate with analysts and data scientists to enable self-service analytics and business reporting. Deliver reliable data integration for regulatory and compliance reporting. Act as a bridge between technical teams and business leaders, ensuring alignment and impact. Qualifications & Experience: Education: Bachelor's degree in Computer Science, Engineering, Information Systems, or related technical field. Advanced degree or relevant certifications (e.g., SnowPro, AWS/Azure Data Engineer, Databricks) preferred. Experience: 7+ years in data engineering roles with at least 3 years on cloud data platforms. Demonstrated expertise with Snowflake and at least one major cloud platform (AWS or Azure). Hands-on experience in upstream oil & gas data (wells, completions, SCADA, production volumes, reserves, etc.). Strong track record of delivering operational and analytical data pipelines. Skills & Competencies: Advanced SQL Server and Python skills. Strong background in data modeling, ETL/ELT, cataloging, lineage, and security. Familiarity with orchestration tools (Airflow, Azure Data Factory, etc.). Proficiency with CI/CD pipelines, version control (Git), and automated testing practices. Experience with BI and visualization tools (Power BI, Spotfire, Tableau). Understanding of AI/ML concepts and preparing datasets for analytics. Familiarity with Agile methodology and Scrum framework; able to work in iterative sprints and adapt to changing priorities. Strong communication and stakeholder engagement skills, with the ability to influence both executives and technical peers. Knowledge of data governance, security standards, and regulatory compliance within the energy sector. Crescent Energy is an equal opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, gender/pregnancy, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status or any other legally protected status. Crescent Energy is also committed to compliance with all fair employment practices regarding citizenship and immigration status. If you require accommodation to complete the application process, please let us know by contacting ****************************

Must Have Technical/Functional Skills * Strong experience in SDLC delivery, including waterfall, hybrid and Agile methodologies. Experience delivering in an agile environment, * Experience of implementing and delivering data solutions and pipelines on AWS Cloud Platform - using Redshift * Strong in Python hands on experience. Not expected to code in depth but lead a team of developers and provide thought leadership, guidance and recommendations. * Apache Airflow experience is a plus * A strong understanding of data modelling, data structures, databases, and ETL process and Data wharehousing layers * An in-depth understanding of large-scale data sets, including both structured and unstructured data * Ability to analyze and troubleshoot complex data / SQL issues * Knowledge of ETL (Extract, Transform, Load) processes * Understanding of big data concepts * Knowledge and experience of delivering CI/CD and DevOps capabilities in a data environment Roles & Responsibilities Lead a team of developers, code reviews, suggest improvements in code, provide thought leadership Work on Proposal and POCs, developing prototype and reference models to help in tailoring Offerings & value propositions. Lead, Mentor and groom other team members to work on AWS technologies Generic Managerial Skills, If any Need to have some experience in leading technical team. Salary Range: $100,000 - $115,000 a Year TCS Employee Benefits Summary: Discretionary Annual Incentive. Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans. Family Support: Maternal & Parental Leaves. Insurance Options: Auto & Home Insurance, Identity Theft Protection. Convenience & Professional Growth: Commuter Benefits & Certification & amp; Training Reimbursement. Time Off: Vacation, Time Off, Sick Leave & Holidays. Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing. #LI-DNI