Data Scientist I

Development:

The expectation is that this individual will join the team being foundationally skilled in the following:

• Applying data science fundamentals: data collection, cleansing, exploratory analysis, and visualization.
• Writing Python (pandas, scikit-learn) and SQL to manipulate data and prototype models.
• Conducting hypothesis testing and basic statistical validation to support modeling decisions.
• Using version control (Git) and foundational software engineering practices (modular code, object-oriented design, Docker basics).

The expectation is that this individual will develop proficiency in the following over the course of their tenure:

• Supervised and unsupervised learning techniques, including classification, regression, and basic clustering.
• Time-series and forecasting fundamentals, developed under senior guidance.
• Packaging and serving model outputs via Docker and FastAPI endpoints.
• Writing model cards and validation reports with clear assumptions, metrics, and evaluation summaries.
• Experiment design basics and causal reasoning concepts, developed under mentorship.
• Core data engineering concepts: pipeline basics, schema management, and data contract awareness.

Innovation

• Contribute to proof-of-concept spikes and research explorations (e.g., time-series baselines, optimization heuristics, GenAI/RAG experiments).
• Participate actively in technical brainstorming sessions
• Build small prototypes to test hypotheses and validate modeling approaches before full development.
• Support research initiatives in areas such as LLM/RAG evaluation, generative AI applications, and causal ML under senior direction.
• Apply and contribute to team standards and reusable components as directed by senior scientists.
• Track industry trends and surface relevant ideas with clear evaluation criteria during team discussions.
• Champion responsible AI practices in all modeling and experimentation work.

Execution

• Conduct EDA to ground model design; document data quality issues and surface assumptions before modeling begins.
• Contribute to the full model lifecycle - from training and validation through packaging and handoff - with increasing ownership over time.
• Understand accuracy, scalability, and time-to-value trade-offs; surface these clearly to senior scientists for prioritization decisions.
• Prepare clear model summaries, validation reports, and results presentations for both technical peers and non-technical stakeholders.
• Coordinate with platform teams on packaging and deployment requirements for model services.

Collaboration:

• Actively seek feedback from senior scientists; incorporate code review comments and method guidance to continuously improve modeling quality.
• Partner with Data Science Analysts to ensure data correctness and business context before and during modeling.
• Build collaborative working relationships across the data science team and with domain SMEs; communicate blockers and progress clearly and proactively.

• Bachelor's or Master's degree in Data Science, Data Analytics, Economics, Statistics, Computer Science or a related field involving problem solving and critical thinking, or equivalent work experience.

• 0-3 years (or equivalent graduate coursework or project experience) applying data analysis and modeling to structured problems.

• Working knowledge of core ML algorithms (regression, classification, tree-based methods); familiarity with cross-validation and model evaluation practices.

• Proficiency in Python (pandas, scikit-learn, NumPy) and SQL; familiarity with Git and Docker basics.

• Ability to communicate analytical findings and model trade-offs clearly to technical peers and non-technical collaborators.

• Genuine curiosity about business problems; exposure to supply chain, transportation, or energy domains is a plus.

• Strong analytical reasoning and structured problem-solving skills; able to frame ambiguous questions and test hypotheses systematically.

DIVISION:

U.S. Venture will not offer sponsorship for employment status (including, but not limited to, H-1B, TN, E-3, F1, CPT, OPT, STEM OPT, visa status and other employmentbased nonimmigrant visas) for this position. Accordingly, all applicants must be currently authorized to work in the United States on a fulltime basis and must not require U.S. Venture's sponsorship to continue to work legally in the United States. In general, U.S. Venture does not sponsor candidates for nonimmigrant visas or permanent residency except when there is a specific business need.

U.S. Venture will not accept unsolicited resumes from recruiters or employment agencies. In the absence of an executed recruitment Master Service Agreement, there will be no obligation to any referral compensation or recruiter fee. In the event a recruiter or agency submits a resume or candidate without an agreement, U.S. Venture shall reserve the right to pursue and hire those candidate(s) without any financial obligation to the recruiter or agency. Any unsolicited resumes, including those submitted to hiring managers, shall be deemed the property of U.S. Venture.

U.S. Venture, Inc. is an equal opportunity employer that is committed to inclusion and diversity. We ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender, gender identity or expression, marital status, age, national origin, disability, veteran status, genetic information, or other protected characteristic. If you need assistance or an accommodation due to a disability, you may call Human Resources at (920) 739-6101.