Data Scientist

VOYA Financial Inc. • Braintree, MA

75d

About The Position

We're looking for a versatile Data Scientist to join our growing analytics team. In this role, you'll partner closely with business stakeholders to unlock value from data-whether that's predicting advisor behavior, identifying growth opportunities, or automating manual workflows. You'll be hands-on across the entire data science lifecycle: wrangling data, building and deploying machine learning models, and supporting the MLOps and infrastructure needed to scale solutions across the organization.

This is a high-impact role for someone who blends deep technical skill with business curiosity-and who is passionate about deploying ML models and analytics into the real world.

Requirements

• Bachelor's degree in Data Science, Computer Science, Engineering, or a related quantitative field.
• 5+ years of experience in a data science, ML engineering, or analytics role.
• Strong SQL, Python and ML Techniques programming skills.
• Experience with Azure Cloud, Databricks, and/or Snowflake.
• Experience building and deploying machine learning models in production environments. Hands-on experience with Databricks, including SparkML, and MLflow integration.
• Familiarity with MLOps best practices, including version control, model monitoring, and automated testing.
• Experience with tools such as Git, MLflow, Docker and workflow schedulers.
• Ability to communicate complex technical work to non-technical stakeholders.
• Experience with scalable model training environments and distributed computing.

Nice To Haves

• Master's degree in a quantitative or technical discipline.
• Experience in financial services, fintech, or enterprise B2B analytics.
• Knowledge of A/B testing, causal inference, and statistical experimentation.
• Familiarity with GenAI, LLM pipelines, and vector-based retrieval is a plus and platform like Snowflake Cortex.

Responsibilities

• Analyzing sales and marketing data to identify patterns, trends, and insights that inform strategic decisions and improve campaign effectiveness. The candidate will also need to integrate data from multiple sources to create unified datasets for advanced analysis.
• Clear communication of findings through reports and presentations to stakeholders is crucial to enable informed decision-making. Additionally, developing predictive models and machine learning algorithms to forecast sales performance, client behavior, and marketing ROI.
• Data wrangling & feature engineering: Ingest, clean, and transform data from SQL, APIs, and data lakes (e.g., Snowflake, Databricks). Design robust pipelines that feed into analytics and ML workflows.
• Data understanding & exploration: Work closely with domain experts to deeply understand the meaning, context, quality, and limitations of available datasets. Translate business questions into data requirements and analytics plans.
• Machine learning development: Build, tune, and validate predictive models using scikit-learn, SparkML, XGBoost, or TensorFlow.
• Cross-functional partnership: Collaborate with marketing, sales, and product teams to scope business use cases, define success metrics, and integrate models into operational workflows.
• Model deployment & MLOps: Deploy and manage models using MLflow, docker and CI/CD pipelines. Implement versioning, testing, performance monitoring, and retraining strategies as part of a robust MLOps practice.
• Infrastructure support: Work with data engineering and DevOps teams to maintain and improve model training and deployment infrastructure, including compute resources, workflow orchestration and environment configuration.
• Insight delivery: Build clear, actionable reporting and visualizations using tools like Power BI or Tableau. Focus on impact, not just analysis.

Benefits

• Health, dental, vision and life insurance plans
• 401(k) Savings plan - with generous company matching contributions (up to 6%)
• Voya Retirement Plan - employer paid cash balance retirement plan (4%)
• Tuition reimbursement up to $5,250/year
• Paid time off - including 20 days paid time off, nine paid company holidays and a flexible Diversity Celebration Day.
• Paid volunteer time - 40 hours per calendar year

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Industry: Insurance Carriers and Related Activities
• Number of Employees: 251-500 employees