Data Scientist - Portland - Insight Global

    Insight Global
    Insight Global Portland

    15 hours ago

    Banking / Loans
    Description

    Position: Data Scientist

    Location: Montgomery Park – Portland, OR

    1 Day On-site, 4 Days Remote

    Contract: 6 Month Contract-to-Hire

    Location: Portland (1 day a week)

    JOB DESCRIPTION

    • Develop, deploy, and maintain scalable machine learning models and analytical workflows using Databricks, Apache Spark, and cloud-based data platforms.
    • Partner with financial domain stakeholders to understand business challenges related to risk, compliance, fraud, lending, investments, and customer analytics.
    • Perform hands-on data exploration, feature engineering, statistical analysis, and modeling using Python, SQL, and Spark.
    • Collaborate with data engineering teams to build reliable data pipelines and ensure high-quality, production-ready datasets.
    • Communicate complex technical findings to non-technical audiences; present actionable insights to business leaders.
    • Apply deep financial services expertise to ensure models meet regulatory expectations (e.g., model documentation, audit, transparency, fairness).
    • Optimize workflows for performance and cost efficiency within Databricks and cloud environments.
    • Design experiments and evaluate model performance using best practices in ML Ops, version control, and reproducibility.

    REQUIRED SKILLS AND EXPERIENCE

    • Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Math, Engineering, or related field.
    • 3+ years of experience as a Data Scientist, preferably within banks, credit unions, fintech, or other financial institutions.
    • Hands-on experience with Databricks, Apache Spark, and cloud ecosystems (Azure, AWS, or GCP).
    • Strong proficiency in Python, SQL, and common ML frameworks (scikit‑learn, PyTorch, TensorFlow, etc.).
    • Deep understanding of financial data structures, regulatory requirements, and industry workflows.
    • Experience building, deploying, and monitoring machine learning models in production environments.
    • Ability to translate business problems into data-driven solutions with measurable impact.

    NICE TO HAVE SKILLS AND EXPERIENCE

    • Experience with ML Ops tools (MLflow, Azure DevOps, Databricks Repos, CI/CD pipelines).
    • Familiarity with risk scoring, fraud detection, AML/KYC analytics, credit modeling, or customer segmentation.
    • Knowledge of distributed systems, big data engineering, and scalable architecture design.
    • Strong communication and stakeholder management skills in financial environments.

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