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Python Data Engineer - Machine Learning

Richfield, MN
NorthShore Resources is working with our client on a direct hire opportunity for a Data Engineer. The engineer will work on healthcare delivery R&D projects with a data science team, performing functional prototyping and cloud orchestrating the transfer of successful prototypes to production. The primary focus will be on choosing optimal solutions, and then maintaining, implementing, and monitoring them. This position is part of a growing data science team and will have a unique opportunity to help shape the future of healthcare delivery.

Required Qualifications:
  • Bachelor’s degree in Computer Science Engineering
  • 2+ years of experience in full-stack data science product development: from exploratory data analysis, visualization to ML modeling to application/product development, deployment and maintenance.
  • Strong problem-solving skills with an emphasis on product development.
  • Strong knowledge of statistical techniques/concepts and experience applying them (regression, properties of distributions, statistical tests, etc).
  • Strong experience with a variety of machine learning algorithms and an understanding of their real-world advantages/drawbacks.
  • Excellent written and verbal communication skills.
  • Team player. Comfortable with collective decision making; learning from and mentoring others; participation in code/experiment reviews; and collective ownership of code.
  • Genuine interest in developing knowledge and solutions that will contribute to affordable,
    high-quality healthcare.
  • Great to have experience:
    • Pandas
    • statsmodels
    • scikit-learn
    • gradient boosting libraries: XGBoost, CatBoost, LightGBM
    • plotting libraries: Matplotlib, seaborn, Plotly
    • dashboarding solutions: Panel, Dash
    • hyperparameter optimization tools: Optuna, HyperOpt
    • Airfl
Accountabilities:
  • Identify, collect and wrangle structured and unstructured data from databases, files and third-party APIs. (SQL, unix shell, python, pandas)
  • Developing, modelling, deploying and supporting pipelines and applications, ideally in Python
  • Build and tune machine-learning models and pipelines (python, pandas, scikit-learn, xgboost).
  • Writing clean, tested, documented code for collective review and ownership to solve business problems.
  • Configuration and deployment of Docker containers.
  • Document experiment findings (python, Jupyter notebooks)
  • Implement shared Python packages for cross-project functionality.
  • Translating staffing forecast data to understand outliers in data, understanding shift, case mix and future staffing needs.
  • Develop processes and tools to monitor and analyze model performance and data accuracy (python).
  • Collaborate with other data scientists/ml engineers, developers, dev/ops, business stakeholders, etc. (Jupyter, Jira, Wiki)
  • Perform other duties as assigned.
  • Participates in technology roadmap discussions and planning.

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