Senior Director, Data Science - job 3 of 43

As a Senior Director of Data Science at Visa, your primary responsibilities include leading a data science team that supports key bank and merchant partners. You'll oversee project management, ensuring smooth execution from conception to completion while managing a portfolio of 5 to 10 projects simultaneously. Additionally, you’ll foster the development of your team through coaching and professional guidance, engage in vendor management, and cultivate strategic relationships with Visa client leadership to identify impactful business opportunities.

To qualify for the Senior Director of Data Science role at Visa, candidates typically need extensive experience in data science and leadership, with a strong background in managing teams of data scientists. Applicants should possess exceptional analytical skills, with the ability to handle large data sets and develop predictive models. Furthermore, excellent communication skills are essential, as you will need to articulate findings and strategies across various levels within the organization and to external clients.

In this role, the Senior Director of Data Science at Visa is expected to proactively engage with clients through regular strategic planning discussions. You'll cultivate and manage a pipeline of work, ensuring that projects align with client needs and drive significant business impact. Building relationships with both internal and external stakeholders is crucial, as it helps in executing projects effectively while leveraging Visa’s extensive resources.

As a Senior Director of Data Science at Visa, you’ll work within a complementary team environment that includes members from various groups in the company. You will manage a diverse team of 5 to 7 data professionals and collaborate closely with peers in other functional areas like marketing and analytics. This encourages a rich exchange of ideas and solutions, promoting both professional growth and innovation in tackling business challenges.

The work environment for a Senior Director of Data Science at Visa is hybrid, offering flexibility to balance in-office and remote work. Days in the office will be confirmed by your Hiring Manager, promoting a culture that values both collaboration and the autonomy to perform tasks effectively. The dynamic workplace is designed to foster innovation and creativity, making it a stimulating environment for a seasoned professional.

When answering this question, detail your past experiences managing teams, including the number of team members you led and specific projects you accomplished together. Highlight your leadership style and how you fostered collaboration, pointed out professional development initiatives you implemented, and share metrics that demonstrate the success of your team.

In your response, discuss the criteria you use to evaluate and prioritize projects, such as impact on business goals, client needs, and resource availability. Explain how you communicate these priorities to your team and how you adjust timelines or resources when necessary to ensure successful project completion.

Provide a comprehensive overview of the analytical techniques you excel in, like regression analysis, machine learning models, or data visualization tools. Share specific examples of how you applied these techniques to solve business problems and the results that ensued, emphasizing their impact on decision-making.

Focus on your ability to simplify complex data insights when answering this question. Share a specific instance where you successfully communicated findings, the methods you used to make the data relatable, and the feedback you received from your audience. Highlight your communication skills and adaptability.

Discuss your strategies for building rapport with stakeholders, emphasizing the importance of understanding their needs and expectations. Provide examples of how you maintained communication, solicited feedback, and navigated challenges while ensuring alignment on project goals.

Explain the step-by-step process you follow in creating predictive models, such as data collection, cleansing, feature selection, modeling, and validation. Share a specific project where you developed a model that provided significant insights or improved business outcomes.

When responding, emphasize strategies you’ve used to encourage creativity and innovation, such as brainstorming sessions, hackathons, and encouraging team members to share new ideas without fear. Highlight tangible examples where such initiatives led to successful outcomes.

Be prepared to discuss significant challenges, whether it’s managing team dynamics, resource constraints, or communicating technical information effectively. Illustrate your problem-solving approach and resilience, sharing the outcomes of your efforts.

Offer a compelling example of a project where your data analysis or predictive modeling made a tangible difference for a business. Discuss the steps you took, the data involved, and the measurable impact this had on the business's bottom line.

Outline the specific tools and technologies you are proficient in, such as programming languages (e.g., Python, R), data visualization tools, or big data platforms. Explain how you stay updated on new technologies and how you assess which tools fit best for various projects.