• Deeply understand business needs and translate business needs to a technical project. • Identify appropriate data sources to use. Perform data aggregations and feature engineering as needed. • Write Python programming code to make visualizations, build and implement models. • Be flexible and open to innovative ideas and alternative ways of solving problems. • Present the results to non-tech partners and influence them to use predictive models. • Develop, validate, and deploy advanced machine learning models to predict business outcomes and inform strategic and operational decisions. • Build and evaluate predictive models used in production systems, including real-time scoring and model-driven product workflows. • Assess model impact via A/B testing and other experimental methods to optimize business outcomes. • Stay abreast of industry best practices and state-of-the-art methodology in data science.

• You will design, implement, and evaluate advanced natural language understanding (NLU) systems that interpret complex clinical text and support data-driven medical decision making • Collaborate closely with clinical domain experts, fellow data scientists, ML engineers, and product teams to bring research prototypes into production systems • Explore new modeling approaches, optimize training pipelines, and contribute to the long-term direction of Solventum’s deep learning portfolio • Scoping and designing NLP/NLU applications that support clinical understanding of medical documents and downstream healthcare workflows • Translating business and clinical requirements into mathematical and experimental criteria, ensuring models are measurable, reliable, and auditable • Processing, aligning, and enriching diverse structured and unstructured medical datasets for deep learning, LLMs, and agentic AI systems • Developing and evaluating deep learning models, including transformer-based architectures and neural architectures such as CNNs and attention mechanisms for capturing linguistic patterns in clinical text • Understanding and mitigating model weaknesses, including bias, drift, hallucination behavior, and robustness concerns • Designing experiments and error analyses that explain model behavior and enable clear communication with both technical and non-technical audiences • Deploying models into Solventum's cloud environment, partnering with ML engineering to ensure reliability, observability, and compliance within regulated healthcare systems • Staying current with emerging research in NLP/LLMs, evaluating new methods and identifying opportunities to advance Solventum’s deep learning initiatives

ABOUT THE TEPA COMPANIES Established in 2005 and owned by the Paskenta Band of Nomlaki Indians, The Tepa Companies deliver comprehensive and sustainable solutions to federal, state, local, and private-sector clients throughout the United States. The tribally owned companies work independently and collaboratively to provide wide-ranging construction, engineering, environmental, industrial, staffing, and technology services. When you join Tepa Companies, you have the opportunity to expand your entrepreneurial skill set while growing professionally alongside the best in the industry. You will have the opportunity to impact your team, the organization as a whole, and subsequently, our Tribe. We seek out top talent to provide the best services for our clients. We focus on being a responsible company for our employees and their families by creating a culture that reflects our core values and offering competitive pay and benefits package. Our benefits package includes comprehensive medical, dental, vision, generous paid time off and holidays, 401(k) plan with company match, life insurance, flexible spending and health savings account, mental health support and resources, short and long-term disability, and tuition reimbursement. The Tepa Companies are seeking a Project Environmental Data Scientist to lead the design, delivery, and operation of environmental data systems across multiple projects, ensuring that data pipelines, analytics, and reporting processes support accurate and defensible decision-making. This role operates within an Agile delivery environment and is responsible for coordinating technical execution, managing project-level data systems, and maintaining alignment with the organization’s single source of truth (SSOT). The position integrates data architecture, analytics, and project delivery to ensure consistent, scalable, and high-quality outcomes. Job Functions: - Leads the planning, execution, and delivery of environmental data systems, including databases, pipelines, analytics, and reporting workflows across multiple projects. - Ensures alignment of project data systems with enterprise data architecture and SSOT standards. - Oversees environmental data management, analysis, and system operations to ensure data quality, consistency, and traceability. - Directs and mentors data scientists and analysts, providing technical guidance and ensuring delivery of production-ready outputs. - Coordinates with clients, contractors, and internal teams to define requirements, develop solutions, and implement data-driven systems. - Prepares proposals, scopes of work, and cost estimates for data-related components of projects. - Manages project schedules, deliverables, and priorities within an Agile delivery framework. - Leads the development and implementation of automated workflows and data pipelines to improve efficiency and scalability. - Ensures that analytical outputs and data products support regulatory, programmatic, and decision-making needs. - Identifies risks, data gaps, and system limitations, and develops mitigation strategies. - Supports and oversees QA/QC processes, including coordination with laboratories and data validation teams. - Supports proposals and contributes technical input to scopes and solutions. - Documents and standardizes workflows to support repeatable and scalable delivery across projects. WHAT WE’RE LOOKING FOR - Bachelor’s degree in data science, environmental science, engineering, computer science, or related field - 7-10 years of relevant experience - 0-5 years of demonstrated experience designing and implementing data systems, pipelines, and analytical solutions for environmental data - Strong ability to design and manage data systems, including databases, pipelines, and automated workflows - Proficiency in data tools such as SQL, Python, or similar technologies - Ability to lead technical teams and coordinate delivery across multiple projects - Strong analytical and problem-solving skills with focus on data quality and system performance - Strong communication skills with ability to translate technical outputs into actionable insights - Ability to manage competing priorities and deliver results within an Agile environment - Must be able to pass a law enforcement/financial background check for access to military and government facilities, as needed. Preferred not required: - Masters preferred - Experience with environmental regulatory programs (CERCLA, BRAC, FUDS, etc.) - Familiarity with cloud-based data platforms - GIS familiarity is acceptable but not required

• Empower the company with data - Generate and communicate data-driven insights to influence product and business decisions. • Develop metrics and experiments - Understand our growth and measure the impact of product and operational changes. • Work collaboratively - As a member of Growth team, contribute to the company roadmap by working with stakeholders across Product, Engineering, Design, and Operations.