Data Scientist

HF Sinclair Corporation; Dallas (TX); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Medical Insurance

Vision Insurance

Dental Insurance

Paid Time‑Off

401(k) Retirement Plan

Educational Reimbursement

Parental Bonding Time

Employee Discounts

Job summary

HF Sinclair Corporation in Dallas, Texas is seeking an experienced Data Scientist to develop and improve production AI/ML solutions that support enterprise decision‑making and automation. You will own model development, evaluation, and deployment across business use cases.

You will collaborate with data engineering and engineering teams, apply NLP/LLMs, build reproducible pipelines, ensure responsible AI practices, and mentor junior data scientists in a fast‑paced environment.

Qualifications

• 5+ years of hands-on experience in applied data science, ML, or AI including model development.
• Bachelor's degree in a related field or equivalent work experience.

Responsibilities

• Translate business challenges into AI/ML use cases with measurable criteria.
• Design, train, validate, and optimize ML models using structured/unstructured data.
• Evaluate and fine-tune models, including NLP and large language models.
• Build GenAI/Agentic AI solutions with retrieval workflows and guardrails.
• Develop reproducible pipelines and productionize solutions with controls.
• Monitor model performance, drift, latency, and costs; drive improvements.

Skills

Python & SQL

NLP & Generative AI

ML Dev & Deployment

Cloud services

Data engineering

Model evaluation

Education

Bachelor's degree

Tools

MLflow

Kubeflow

Docker

Kubernetes

LangSmith

Job description

Basic Function

HF Sinclair's Data Scientist develops and continually improves production artificial intelligence (AI) and machine learning (ML) solutions that support enterprise decision-making and automation. This hands‑on technical role spans business problem definition, experimentation, model development, deployment, and ongoing evaluation.

The role applies statistics, traditional machine learning, deep learning, generative AI, and agentic AI to enterprise use cases. The Data Scientist owns model development, evaluation, and continuous improvement; partners with engineering teams on deployment and operational controls; and mentors junior data scientists while collaborating with business and client‑facing teams.

Job Duties

• Translate business challenges into clearly defined AI/ML use cases, measurable success criteria, appropriate evaluation methods, and feasible technical approaches.
• Data quality and readiness: Assess data completeness, accuracy, representativeness, and potential leakage before developing models.
• Design, train, validate, and optimize machine learning models using structured and unstructured data; conduct exploratory analysis, feature engineering, statistical testing, and error analysis.
• Evaluate, adapt, and fine‑tune pre‑trained models, including NLP, deep learning, and large language models (LLMs), for specific enterprise and domain requirements.
• Build and improve GenAI and Agentic AI solutions, including retrieval‑based workflows, tool integration, agent orchestration, evaluation, guardrails, and human‑in‑the‑loop review where appropriate.
• Develop reproducible training and evaluation pipelines, and work with engineering teams to productionize solutions with appropriate versioning, deployment, and operational controls.
• Own continuous improvement of deployed models and AI agents: monitor accuracy, reliability, drift, unexpected behavior, latency, and cost; investigate issues and drive model refinement or retraining.
• Collaborate with data engineering, application, platform, and business teams to deliver secure, scalable, explainable, and maintainable solutions.
• Apply responsible AI practices, including transparency, model observability, governance, documentation, and appropriate privacy and risk controls.
• Document architectural choices, experiments, model limitations, and reusable approaches; conduct technical reviews and mentor junior data scientists.
• Communicate results, trade‑offs, risks, and business impact to technical and non‑technical stakeholders; contribute technical expertise to solution design and presales discussions.

Special assignments or tasks assigned to the employee by their supervisor, as determined from timeto time in their sole and complete discretion.

Experience

• Six or more years of hands‑on experience in applied data science, machine learning, or AI, including responsibility for model development and production deployment or support.

Education Level

A minimum of a Bachelors Degree in Chemical Engineering, Mechanical Engineering, Computer Science or other related fields, or equivalent work experience in lieu of a four‑year degree is required

Required Skills

• Proficiency in Python and SQL, with practical experience in data processing, model development, and machine learning libraries such as pandas, scikit‑learn, PyTorch, or TensorFlow.
• Ability to apply statistical methods, supervised and unsupervised learning, feature engineering, experiment design, model selection, and rigorous evaluation.
• Hands‑on experience with NLP and generative AI techniques, including LLMs, prompt engineering, retrieval‑augmented generation, and model adaptation or fine‑tuning.
• Experience developing or integrating AI agents and evaluating their quality, reliability, and behavior in enterprise workflows.
• Understanding of production machine learning practices, including reproducible pipelines, model registries, versioning, monitoring, troubleshooting, and retraining.
• Experience working with complex structured and unstructured datasets.
• Familiarity with cloud services such as AWS, Azure, or Google Cloud Platform (GCP), application programming interfaces (APIs), and container‑based deployment concepts.

Preferred Skills

• Familiarity with production machine learning tools such as MLflow or Kubeflow.
• Exposure to Snowflake or similar enterprise data platforms.
• Familiarity with Docker, Kubernetes, or continuous integration and continuous delivery (CI/CD) practices.
• Experience with LLM observability and evaluation tools such as LangSmith or Langfuse, and with enterprise AI security and governance requirements.
• Analytical and problem‑solving skills, including the ability to translate ambiguous requirements into practical, measurable solutions.
• Technical ownership and engineering judgment, including the ability to balance model quality, explainability, delivery effort, and operating constraints.
• Clear communication, client and stakeholder engagement, cross‑functional collaboration, and technical mentorship skills.
• Curiosity and adaptability, with a disciplined approach to evaluating and applying emerging AI capabilities.

Benefits

HF Sinclair offers a comprehensive benefits package designed to support the well‑being of our employees and their families. Our benefits include, but are not limited to, the following:

• Medical Insurance
• Vision Insurance
• Dental Insurance
• Paid Time‑Off
• 401(k) Retirement Plan with match
• Educational Reimbursement
• Parental Bonding Time
• Employee Discounts

We are committed to fostering a supportive and inclusive work environment, ensuring our employees have the resources needed to thrive professionally and personally. Benefit eligibility is governed by official plan documents, for more details visitTotal Rewards.

Our One HF Sinclair Culture:

At HF Sinclair, we are united through our One HF Sinclair Culture, which is underpinned by our five core values of Safety, Integrity, Teamwork, Ownership and Inclusion. Developed to empower our people, our five core cultural values are at the heart of everything we do and extend to how we engage our stakeholders. These values influence our decisions, shape our behaviors and keep us connected across the entire organization. We maintain a true Safety culture for our employees, communities, environments and customers. Our goal is to make sure everyone returns home safely each day. We have a long‑standing commitment to Integrity and ethical behavior and do what is right for our employees, investors, communities and the environment. We encourage employees to Step Up and Stand Out by championing a culture of Teamwork and Ownership. We foster a culture of Inclusion by encouraging diversity of experiences, viewpoints and backgrounds. What makes each of us different, together makes us stronger.

About HF Sinclair Corporation

HF Sinclair Corporation, headquartered in Dallas, Texas, is an independent energy company that produces and markets high‑value light products such as gasoline, diesel fuel, jet fuel, renewable diesel and lubricants and specialty products. HF Sinclair owns and operates refineries located in Kansas, Oklahoma, New Mexico, Wyoming, Washington and Utah. HF Sinclair provides petroleum product and crude oil transportation, terminalling, storage and throughput services to our refineries and the petroleum industry. HF Sinclair markets its refined products principally in the Southwest U.S., the Rocky Mountains extending into the Pacific Northwest and in other neighboring Plains states and supplies high‑quality fuels to more than 1,750 branded stations and licenses the use of the Sinclair brand to more than 350 additional locations throughout the country. HF Sinclair produces renewable diesel at two of its facilities in Wyoming and also at its facility in New Mexico. In addition, subsidiaries of HF Sinclair produce and market base oils and other specialized lubricants in the U.S., Canada and the Netherlands, and export products to more than 80 countries.

Equal Opportunity Employer

HF Sinclair Corporation is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status or any other prohibited ground of discrimination.