Data scientist jobs in Galveston, TX

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.

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

Relevant experience to be more than 8-9 years, Strong and proficient in Databricks, DLT (Delta Live Tables) framework and Pyspark, need excellent communication Thanks Aatmesh *************************

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

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

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

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

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

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

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

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

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

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

MINIMUM QUALIFICATIONS Education: Bachelor's Degree in science, engineering, computer science, mathematics, statistics, or related STEM field required. Master's Degree in Data Science preferred. Licenses\/Certifications: (None) Experience \/ Knowledge \/ Skills: Seven (7) years of experience in data science is required Professional experience in hospital setting, medical informatics, healthcare information technology\/finance\/revenue cycle data management, or Electronic Health Record (EHR) data management is preferred Business analytical skills (process flows, procedures, spreadsheets, modeling, etc.), technical expertise, mathematical skills and good understanding of design and architecture principles are required Possesses deep understanding of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real\-world advantages\/drawbacks Proficient understanding of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications Ability to communicate, gather requirements and execute storytelling with data Possesses advanced level knowledge of the data science project life cycle Proficient programming skills in addition to a working knowledge and experience of statistical analysis tools Demonstrates proficiency in problem solving, analytical reasoning and decision\-making skills Demonstrates proficiency in identifying and seeking needed information to perform problem\/situation analysis Advanced level of understanding and experience in researching and resolving data issues with a logical, instinctive, and problem\-solving mentality working with large, complex and incomplete sources Exhibits strong project management skills, with an ability to work independently on multiple projects with competing priorities and a strong commitment to meeting goals and deadlines Advanced understanding of SQL database management tools Exceptional analytical skills and ability to understand and interpret results based on advanced statistical techniques Strong written and verbal communication skills in IT and business environments; ability to communicate to technical and non\-technical audiences Ability to work under minimal supervision in a fast\-paced multidisciplinary environment Advanced knowledge of data science methods - time series forecasting, linear regression, A\/B testing, statistical testing, Clustering, etc. Superior customer service in the form of first\-rate work products and project management Strong ability to manage challenging client situations Strong ability to troubleshoot and recommend solutions Strong ability to translate complex information for a wide range of stakeholders PRINCIPAL ACCOUNTABILITIES Leads high priority projects that impact the organization. Leads complex issues and problems, and refers more complex issues to higher\-level staff. Provides technical supervision\/mentoring to other data scientists and trains the broader audience on data science developments. Provides leadership, coaching, and\/or mentoring to subordinate group. Develops custom data models and algorithms to apply to data sets. Develops and applies algorithms or models to key business metrics with the goal of improving operations or answering business questions. Provides findings and analysis for use in decision making. Performs research, analysis, and modeling on organizational data. Maintains existing models and evaluates their goodness of fit. Provides in\-depth data insights from structured and unstructured data for complex business problems through use of advanced analytics techniques, predictive modeling, data mining\/visualization and pattern analysis tools. Develops and tests hypotheses and communicates findings in clear, precise and actionable manner to project and leadership teams. Works closely with teams to identify, understand, and resolve data issues and improve efficiency, productivity and scalability of data processes. Assists with the evaluation of data science vendors and tools. Ensures safe care to patients, staff and visitors; adheres to all **** policies, procedures, and standards within budgetary specifications including time management, supply management, productivity and quality of service. Promotes individual professional growth and development by meeting requirements for mandatory\/continuing education and skills competency; supports department\-based goals which contribute to the success of the organization; serves as preceptor, mentor and resource to less experienced staff. Demonstrates commitment to caring for every member of our community by creating compassionate and personalized experiences. Models Companservice standards by providing safe, caring, personalized and efficient experiences to patients and colleagues. Other duties as assigned. 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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.

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