Job Description
JDevelop, 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.
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.
Required Skills & 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 & 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.
Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.