Data scientist jobs in Texas City, TX

A Data Scientist supporting AI/ML and LLM-driven solutions to build, deploy, and optimize advanced models for operational decision-making. Day-to-Day Responsibilities: Design, train, and fine-tune machine learning, deep learning, and LLM models Collect, process, and analyze structured/unstructured datasets Engineer features to improve predictive model performance Develop NLP and LLM-based applications (prompt engineering, fine-tuning, inference) Deploy and monitor ML models using MLOps best practices Build dashboards and presentations to communicate insights Collaborate with stakeholders to translate data insights into business strategy Requirements: Must-Haves: Snowflake, SQL, Palantir (or similar operational AI decision platform) Strong AI/ML and LLM foundation Experience with NLP, deep learning, and predictive modeling Python proficiency and experience with PyTorch, TensorFlow, Hugging Face Strong SQL and data engineering skills AWS experience (SageMaker, S3, Redshift) and ML pipeline automation Nice-to-Haves: Graduate degree in a quantitative field Experience with Power BI, Dash, or Streamlit Benefits: This role is eligible to enroll in both Mondo's health insurance plan and retirement plan. Mondo defers to the applicable State or local law for paid sick leave eligibility

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

We are looking for a talented and motivated Python Data Engineers. We need help expanding our data assets in support of our analytical capabilities in a full-time role. This role will have the opportunity to interface directly with our traders, analysts, researchers and data scientists to drive out requirements and deliver a wide range of data related needs. What you will do: - Translate business requirements into technical deliveries. Drive out requirements for data ingestion and access - Maintain the cleanliness of our Python codebase, while adhering to existing designs and coding conventions as much as possible - Contribute to our developer tools and Python ETL toolkit, including standardization and consolidation of core functionality - Efficiently coordinate with the rest of our team in different locations Qualifications - 6+ years of enterprise-level coding experience with Python - Computer Science, MIS or related degree - Familiarity with Pandas and NumPy packages - Experience with Data Engineering and building data pipelines - Experience scraping websites with Requests, Beautiful Soup, Selenium, etc. - Strong understating of object-oriented design, design patterns, SOA architectures - Proficient understanding of peer-reviewing, code versioning, and bug/issue tracking tools. - Strong communication skills - Familiarity with containerization solutions like Docker and Kubernetes is a plus

About the Role The Senior Data Engineer will play a critical role in building and scaling an enterprise data platform to enable analytics, reporting, and operational insights across the organization. This position requires deep expertise in Snowflake and cloud technologies (AWS or Azure), along with strong upstream oil & gas domain experience. The engineer will design and optimize data pipelines, enforce data governance and quality standards, and collaborate with cross-functional teams to deliver reliable, scalable data solutions. Key Responsibilities Data Architecture & Engineering Design, develop, and maintain scalable data pipelines using Snowflake, AWS/Azure, and modern data engineering tools. Implement ETL/ELT processes integrating data from upstream systems (SCADA, production accounting, drilling, completions, etc.). Architect data models supporting both operational reporting and advanced analytics. Establish and maintain frameworks for data quality, validation, and lineage to ensure enterprise data trust. Platform Development & Optimization Lead the build and optimization of Snowflake-based data warehouses for performance and cost efficiency. Design cloud-native data solutions leveraging AWS/Azure services (S3, Lambda, Azure Data Factory, Databricks). Manage large-scale time-series and operational data processing workflows. Implement strong security, access control, and governance practices. Technical Leadership & Innovation Mentor junior data engineers and provide technical leadership across the data platform team. Research and introduce new technologies to enhance platform scalability and automation. Build reusable frameworks, components, and utilities to streamline delivery. Support AI/ML initiatives by delivering production-ready, high-quality data pipelines. Business Partnership Collaborate with stakeholders across business units to translate requirements into technical solutions. Work with analysts and data scientists to enable self-service analytics and reporting. Ensure data integration supports regulatory and compliance reporting. Act as a bridge between business and technical teams to ensure alignment and impact. Qualifications & Experience Education Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field. Advanced degree or relevant certifications (SnowPro, AWS/Azure Data Engineer, Databricks) preferred. Experience 7+ years in data engineering roles, with at least 3 years on cloud data platforms. Proven expertise in Snowflake and at least one major cloud platform (AWS or Azure). Hands-on experience with upstream oil & gas data (wells, completions, SCADA, production, reserves, etc.). Demonstrated success delivering operational and analytical data pipelines. Technical Skills Advanced SQL and Python programming skills. Strong background in data modeling, ETL/ELT, cataloging, lineage, and data security. Familiarity with Airflow, Azure Data Factory, or similar orchestration tools. Experience with CI/CD, Git, and automated testing. Knowledge of BI tools such as Power BI, Spotfire, or Tableau. Understanding of AI/ML data preparation and integration.

Python Data Engineer - Houston, TX (Onsite Only) A global energy and commodities organization is seeking an experienced Python Data Engineer to expand and optimize data assets that support high-impact analytics. This role works closely with traders, analysts, researchers, and data scientists to translate business needs into scalable technical solutions. The position is fully onsite due to the collaborative, fast-paced nature of the work. MUST come from an Oil & Gas organization, prefer commodity trading firm. CANNOT do C2C. Key Responsibilities Build modular, reusable Python components to connect external data sources with internal tools and databases. Partner with business stakeholders to define data ingestion and access requirements. Translate business requirements into well-designed technical deliverables. Maintain and enhance the central Python codebase following established standards. Contribute to internal developer tools and ETL frameworks, helping standardize and consolidate core functionality. Collaborate with global engineering teams and participate in internal Python community initiatives. Qualifications 7+ years of professional Python development experience. Strong background in data engineering and pipeline development. Experience with web scraping tools (Requests, BeautifulSoup, Selenium). Hands-on Oracle/PL SQL development, including stored procedures. Strong grasp of object-oriented design, design patterns, and service-oriented architectures. Experience with Agile/Scrum, code reviews, version control, and issue tracking. Familiarity with scientific computing libraries (Pandas, NumPy). Excellent communication skills. Industry experience in energy or commodities preferred. Exposure to containerization (Docker, Kubernetes) is a plus.

We are currently seeking a Data Engineer to join the Big Data and Advanced Analytics department. As part of the Data Engineering team, the Data Engineer will work closely with the Data Science team and Business functions to solve real-world oil and gas midstream problems using machine learning, data science and artificial intelligence. This individual will provide technical and thought leadership to the team to build out a data engineering practice within the organization. Must Have Skills Python Pandas, Numpy, Pytest, Scikit-Learn SQL Apache Airflow Kubernetes CI/CD Git Test Driven Development (TDD) API development Knowledgeable of Machine Learning Responsibilities Create, test, and maintain data pipeline architectures Work independently on analytic projects for multiple business functions Automate manual data flows for repeated use and scalability Develop data-intensive applications with API's Develop algorithms to transform data into useful, actionable information Operationalize mathematical models and machine learning models Assist data analysts and data scientists with data processing automation and deployment Implement data quality checks to ensure data accuracy and consistency

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

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

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!

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

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

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

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 Responsibilities 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 service standards by providing safe, caring, personalized and efficient experiences to patients and colleagues. Other duties as assigned. Minimum Qualifications Education Bachelors Degree in science, engineering, computer science, mathematics, statistics, or related STEM field required. Masters 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 Benefits Dental Insurance, Medical Insurance, Vision Insurance, Life Insurance, Retirement, Equity, PTO,

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

Linqx is an industry-leading provider of end-to-end digital solutions and analytics for the oil and gas sector, leveraging advanced data analytics to optimize engineering and operations​. Its cloud-based platforms deliver AI-driven insights that enhance reservoir performance and streamline workflows​​. Driven by a mission of data-driven innovation​, Linqx combines cutting-edge technology with oilfield expertise to deliver transformative results​. Position Summary: Seeking an experienced and highly skilled Data Scientist to join our dynamic team. The ideal candidate will possess a strong foundation in data science, machine learning, and data engineering, with a particular focus on developing and deploying cutting-edge generative AI models. Incumbents will work closely with cross-functional teams to drive impactful data-driven decisions and innovations across the organization. Our dynamic approach to technology offers an exciting environment for this role that's focused on big data, machine learning, and advanced analytics. Key Roles / Responsibilities: Design, implement, and deploy advanced machine learning models and algorithms, particularly in Generative AI (e.g., GANs, transformers, diffusion models). Leverage deep learning frameworks (such as TensorFlow, PyTorch, or JAX) to build and train state-of-the-art models for natural language processing (NLP), computer vision (CV), and other generative tasks. Collaborate with engineering teams to ensure seamless integration of AI/ML solutions into production environments, optimizing for performance and scalability. Work with technology and business leaders to evolve data-driven vision, communication channels, and all supporting documentation Utilize advanced statistical techniques and data modeling methods to analyze large, complex datasets and provide actionable insights. Develop data pipelines for cleaning, processing, and transforming raw data into structured formats suitable for machine learning applications (i.e. familiarity with Lakehouse deployment/governance on Medallion architecture). Design, build, and maintain efficient and scalable data architectures and data storage solutions. Work on end-to-end machine learning workflows, including data preprocessing, feature engineering, model training, evaluation, and deployment. Continuously evaluate and optimize model performance and contribute to improving the overall AI/ML infrastructure and processes. Mentor and/or manage junior data scientists and engineers, fostering a culture of collaboration and continuous learning. Stay updated on the latest advancements in AI/ML research and apply innovative techniques to solve business problems. Document and communicate findings and solutions clearly to both technical and non-technical stakeholders. Participate and potentially drive data-specific technology selection activities Required Education, Experience, and Qualifications: Master's or PhD in Computer Science, Data Science, Engineering, or a related field, with a focus on machine learning, AI, or data engineering. Proven expertise in Generative AI, including experience with techniques such as GANs, VAEs, transformers, RAGs, and other advanced AI and deep learning models. Strong proficiency in programming languages like Python, R, or Julia, and hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn, etc.). Extensive experience with data engineering, including data wrangling, ETL processes, data storage, and real-time data processing. In-depth knowledge of machine learning algorithms, deep learning, and statistical modeling techniques. Familiarity with cloud platforms (AWS, GCP, or Azure) and distributed computing frameworks (e.g., Spark, Hadoop). Experience in designing and optimizing data architectures for both batch and real-time data flows. Proficient with database systems (SQL, NoSQL) and data query languages. Strong problem-solving, analytical, and critical-thinking skills with the ability to work independently or as part of a team. Excellent communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences. Preferred Skills: Knowledge of NLP and CV applications, including experience with large-scale pre-trained models like GPT, BERT, or DALL·E. Expertise in model deployment and monitoring in production environments (e.g., Docker, Kubernetes, MLflow). Experience with version control systems (e.g., Git) and software development best practices. Familiarity with DevOps practices and CI/CD pipelines for machine learning projects. Published research in top-tier conferences or journals related to AI/ML or Generative AI. Benefits: Competitive Compensation Package Medical + Dental + Vision Coverage 401K + Company Match Life Insurance + Long Term Disability Coverage - 100% Company Paid Health Savings Account (HSA) Gym Reimbursement Program Tuition Reimbursement Program Wellness Check Program - Insurance Premium Discounts EAP Resources Paid Holidays Paid Time Off (PTO) Working Conditions: Year-round on-site in-office expectation (standard 5-day work week) Working with globally distributed team members and partners Prolonged periods sitting at a desk and working on a computer. Must be able to lift 15 pounds at times. Positions self to install equipment, including under desks. Moves throughout the building to access files. Must be able to comprehend and follow written and oral instructions. Must be able to complete tasks even with frequent interruptions. Must be able to use discretion and independent judgment as needed. Must be able to speak clearly on the phone and to fellow workers. This job description should not be interpreted as an exhaustive list of responsibilities or as an employment agreement between the employer and the employee. The above statements are intended to describe the general nature and level of work being performed by employees assigned to this classification and are subject to change as the needs of the employer and requirements of the job change. Any essential functions of this position will be evaluated as necessary should an employee/applicant be unable to perform the functions or requirements due to a disability as defined by the Americans with Disabilities Act (ADA). Reasonable accommodation for the specific disability will be made for the employee/applicant when possible. I acknowledge that I have read and understand the description of this position and have had the opportunity to ask my supervisor about any points I did not understand. I hereby state that I can perform the essential functions of this position with or without reasonable accommodation.

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