Director, Data Science (Retirement & Wealth)

Together we fight for everyone’s opportunity for a better financial future.

We will do this together — with customers, partners and colleagues.

We will fight for others, not against: We will stand up for and champion everyone’s access to opportunities.

The status quo is not good enough … we believe every individual and every community deserves access to financial opportunities.

We are determined to support both individuals and communities in reaching a better financial future.

We know that reaching this future depends on our actions today.

Like our Purpose Statement, Voya believes in being bold and committed to action.

We are committed to a work environment where the differences that we are born with — and those we acquire throughout our lives — are understood, valued and intentionally pursued.

We believe that our employees own our culture and have a responsibility to foster an environment where we all feel comfortable bringing our whole selves to work.

Purposefully bringing our differences together to positively influence our culture, serve our clients and enrich our communities is essential to our vision.

Are you ready to join a company with a strong purpose and a winning culture? Start your Voyage – Apply Now Role Overview The Director, Workplace Data Science ((Retirement & Wealth) provides strategic leadership for the analytics agenda, identifying high‑value business problems and driving measurable impact.

The team delivers advanced analytics across large business and consumer data sets to generate actionable insights that improve decision‑making, strengthen key relationships, and enhance internal processes.

The role oversees a U.S./India team of analysts and data scientists, guiding solution design, development, deployment, and continuous improvement while setting standards for quality and execution.

The ideal candidate excels at interpreting business needs, applying appropriate data science methods, and communicating insights clearly to stakeholders across functions.