OverviewWe are seeking a Data Scientist to design, build, and deliver predictive analytics, machine learning models, and data-driven insights that support mission and business outcomes. This role requires strong analytical and modeling skills, hands-on experience with ML frameworks, and the ability to collaborate across engineering, data, and product teams. The Data Scientist will contribute to the full lifecycle of model development, from data exploration and feature engineering to model training, evaluation, and deployment, while supporting the articulation of insights and recommendations to technical and non-technical stakeholders.
Contributions
- Conduct exploratory data analysis (EDA) to uncover trends, identify data quality issues, and determine modeling opportunities.
- Develop machine learning models using frameworks such as scikit-learn, XGBoost, PyTorch, TensorFlow, or similar libraries.
- Perform feature engineering, dataset preparation, and model optimization to improve predictive accuracy and operational performance.
- Evaluate models using appropriate statistical methods and performance metrics, documenting findings and informing iterative improvements.
- Work with Data Engineers to understand and enhance data pipelines, ensuring model-ready datasets are accurate, complete, and consistent.
- Collaborate with AI Developers and LLMOps/MLOps Engineers to integrate ML models into production environments or decision-support applications.
- Build visualizations, dashboards, data stories, and executive-friendly summaries to communicate insights clearly to stakeholders.
- Support human-centered design processes by translating user needs into modeling requirements and refining model outputs based on feedback.
- Contribute to reproducibility and auditability by maintaining well-organized code, notebooks, documentation, and experiment histories.
- Stay current with modern data science methodologies, ML techniques, data processing tools, and cloud-enabled analytics workflows.
- You will contribute to the growth of our AI & Data Exploitation Practice!
Qualifications
- Ability to hold a position of public trust with the U.S. government.
- Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Analytics, Engineering, Economics, or a related field.
- 6+ years of experience building and evaluating machine learning models or performing advanced analytics.
- Proficiency in Python and core data science libraries (Pandas, NumPy, scikit-learn, Matplotlib/Seaborn).
- Hands-on experience with at least one modern ML framework (e.g., PyTorch, TensorFlow, XGBoost).
- Experience writing efficient SQL queries and working with structured or semi-structured data in cloud or database environments.
- Familiarity with cloud data and ML platforms such as AWS, Azure, GCP, or Databricks.
- Strong understanding of statistics, probability, experimental design, and model validation techniques.
- Ability to communicate technical concepts clearly to stakeholders and collaborate across multidisciplinary teams.
- Experience with dashboarding tools (Tableau, Power BI) or Python visualization libraries is a plus.
- Curiosity and adaptability, with a drive to stay current in rapidly evolving data and ML practices.
- Relevant certifications (helpful but not required): Databricks Data Scientist Associate, AWS ML Specialty, Azure Data Scientist Associate, Google Professional Data Engineer.
About
steampunk
Steampunk relies on several factors to determine salary, including but not limited to geographic location, contractual requirements, education, knowledge, skills, competencies, and experience. The projected compensation range for this position is $125,000 to $160,000. The estimate displayed represents a typical annual salary range for this position. Annual salary is just one aspect of Steampunk’s total compensation package for employees. Learn more about additional Steampunk benefits here.
Identity Statement
As part of the application process, you are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.
