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Data Science Director (AI & ML)

Company Description

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

Job Description

Visa cards play a crucial role in allowing our commercial solutions partners to pay and be paid. From large enterprises to small businesses, companies depend on Visa to allow their employees ease of operation in the digital payments ecosystem and to provide them with services that can help them gain valuable insights into their customers spending as well as their own spending. The Global Data Science group supports these commercial partners by using our outstandingly rich data set that spans more than 3 billion cards globally and collects more than 100 billion transactions in a single year. Our focus lies on building creative solutions that have an immediate impact on the business of our highly analytical partners. We work in complementary teams comprising members from Data Science and various groups at Visa. To support our rapidly growing group we are hiring a data science director to help grow our commercial solutions business and guide our data scientists in the Bangalore office.

Essential Functions 

  • Drive value from Visa’s unique global data assets to answer critical questions within our Visa Commercial Solutions Team
  • Act as a site leader for all data scientists across various internal IA and Data Science teams, helping to manage the relationship between other offices and continue to grow the team within Bangalore
  • Share learning and leverage best practices across groups
  • Develop Metrics and use dashboards to quantify current state and to monitor progress across markets and segments using consistent definitions
  • Work with partners throughout the organization to find opportunities demonstrating Visa data to drive business solutions
  • Design and develop AI and ML solutions to be applied to solve our stakeholder’s business problems
  • Scope and size opportunities and derive actionable insights for account teams
  • Leverage Forecasting models to enable proactive planning of investments and actions
  • Monitor program effectiveness to ensure value quantification of efforts
  • Draw data-driven insights and make actionable recommendations that reflect the specific business and context
  • Utilize Hadoop, and related query engines such as Hive, Python, Spark to perform advanced data mining
  • Apply statistical solutions to business problems, to develop high-level deliverables and communicate data and technical concepts to a business audience
  • Define detailed analytic scope and methodology, and create analytic plans
  • Execute on the analytic plans with appropriate data mining and analytic techniques
  • Present analytics, insights and recommendations to a non-technical audience
  • Provide mentorship in modern analytic techniques and business applications to unlock the value of Visa’s unique data set, in keeping with market trends, client needs and emerging techniques

This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.

Qualifications

Basic Qualifications
• 15 years of work experience with a Bachelor’s Degree or at least 8 years of work experience with an Advanced Degree (e.g. Master’s, MBA, JD, MD) or at least 3 years of work experience with a PhD degree
Preferred Qualifications
• Minimum of 12 years of analytical experience in applying solutions to business problems
• Post Graduate degree in a Quantitative field
• Hands on experience with one or more data analytics/programming tools such as SAS/Hive/R/SQL/Python
• Prior experience in payments or financial services industry preferred
• Experience in the application of predictive modeling and machine learning techniques
• Demonstrated experience in planning, organizing, and managing multiple analytic projects with diverse cross-functional stakeholders
• Demonstrated ability to innovate solutions to solve business problems
• Results oriented with strong analytical and problem-solving skills, with demonstrated intellectual and analytical rigor
• Good business acumen with strong ability to solve business problems through data driven quantitative methodologies. Experience in payment, retail banking, or retail merchant industries is preferred
• Understanding of Cards/Payments and Banking business model would be a plus
• Team oriented, collaborative, diplomatic, and flexible style, with the ability to tailor data driven results to various audience levels
• Detail oriented, is expected to ensure highest level of quality/rigor in reports & data analysis
• Proven skills in translating analytics output to actionable recommendations, and delivery
• Experience in presenting ideas and analysis to stakeholders
• Exhibit intellectual curiosity and strive to continually learn
• Experience with managing project teams and providing direction and thought leadership

Additional Information

Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.

Average salary estimate

$145000 / YEARLY (est.)
min
max
$120000K
$170000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Data Science Director (AI & ML), Visa

Are you ready to take your leadership skills to the next level as a Data Science Director in AI & ML at Visa? Nestled in the vibrant tech hub of Bangalore, this position puts you at the helm of a team charged with leveraging Visa’s unparalleled global data assets to drive strategic solutions for our commercial partners. Imagine working with a vast data set that spans over 3 billion cards and collects more than 100 billion transactions annually! In this role, you’ll be the site leader for data scientists, ensuring strong collaboration between our offices while nurturing professional growth within the team. Your day-to-day will include crafting AI and ML solutions tailored to meet specific business needs, guiding the analytical scope and methodologies, and presenting your findings to help our stakeholders make informed decisions. The impact you’ll make will resonate across markets. We value a collaborative spirit, encouraging you to share best practices and foster innovation. Plus, this hybrid role offers the flexibility to balance office and remote work, ensuring you’re always in the best environment to unleash your creativity and drive results. If you’re passionate about data and looking to make a significant impact, join us at Visa and embark on a journey of growth and innovation!

Frequently Asked Questions (FAQs) for Data Science Director (AI & ML) Role at Visa
What are the key responsibilities of a Data Science Director at Visa?

As a Data Science Director at Visa, your responsibilities include driving value from Visa's unique global data assets, managing the collaboration between various internal teams, and developing AI and ML solutions tailored to business needs. You'll also scope opportunities, monitor program effectiveness, and provide mentorship on modern analytic techniques. Your role supports both analytical rigor and business innovation.

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What qualifications are required for the Data Science Director position at Visa?

A Data Science Director at Visa typically requires 15 years of work experience with a Bachelor's Degree, or a minimum of 12 years of analytical experience with a Post Graduate degree in a quantitative field. Experience with data analytics tools like SAS, Hive, R, SQL, or Python is essential, along with a strong background in predictive modeling and machine learning techniques, preferably in the payments or financial services industry.

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How does Visa support the growth of data scientists in the Bangalore office?

Visa actively supports the growth of data scientists by creating a collaborative environment where knowledge sharing and mentorship thrive. As a Data Science Director, you’ll play a pivotal role in nurturing the team's development, leveraging best practices, and aligning career growth opportunities with individual team members' aspirations.

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What type of projects will a Data Science Director work on at Visa?

The projects a Data Science Director will work on at Visa involve using advanced data analytics to drive business solutions for commercial partners. This may include designing AI and ML models, analyzing transaction trends, developing forecasting models, and translating complex analytics into actionable insights that align with business objectives.

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What is the hybrid work model like for a Data Science Director at Visa?

The hybrid work model for a Data Science Director at Visa includes alternating between remote work and office presence 2-3 days a week. This approach enables flexibility while ensuring collaboration and connection with team members and stakeholders, allowing you to effectively balance work commitments and personal productivity.

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Common Interview Questions for Data Science Director (AI & ML)
Can you describe your experience with machine learning techniques in the context of data analysis?

When discussing your experience with machine learning, focus on specific projects where you've applied models to solve business problems. Highlight your understanding of various algorithms, choice of tools like Python or R, and how those models impacted decision-making within the organization.

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How have you managed cross-functional teams in past roles?

Share examples of how you effectively led cross-functional teams, emphasizing your communication strategies and conflict resolution skills. Discuss how you ensured alignment between teams with different objectives and how you fostered collaboration to achieve common goals.

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What strategies do you employ for mentoring junior data scientists?

Talk about specific mentoring techniques you find effective, such as setting clear expectations, providing regular feedback, and providing opportunities for hands-on learning. Illustrate with examples of past successes in developing your mentees' skills and career trajectories.

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How do you ensure the quality and rigor of data analysis outputs?

Discuss your process for validating data analysis outputs, which may include peer reviews, following best practices in data cleaning, and utilizing statistical techniques to ensure integrity. Explain how you encourage a culture of quality within your team.

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Can you explain the importance of data-driven decision-making in your previous roles?

Emphasize the transformative power of data-driven decision-making through real-world examples. Talk about how leveraging data insights led to improved business outcomes, helped in strategic planning, and fostered innovation within your team.

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What are the key components of a successful data analytics project?

Outline essential components such as a clear project scope, stakeholder engagement, rigorous data collection and analysis methodologies, and effective communication of findings. Mention how you’ve applied these components in your projects to achieve successful outcomes.

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Describe your experience with presenting complex data insights to non-technical stakeholders.

When answering this, focus on how you've simplified complex technical information into actionable insights. Mention specific techniques you've used to engage your audience and ensure they understand the significance of your findings.

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How do you approach identifying new opportunities for data-driven solutions?

Discuss your approach to staying informed about market trends and business needs, actively seeking feedback from stakeholders, and leveraging data analytics to uncover insights that lead to innovative solutions.

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What tools and technologies are you proficient in for data analytics?

List the data analytics tools and technologies you are skilled in, such as Python, SQL, or Hadoop, and mention specific projects or applications where you utilized these tools effectively to demonstrate your expertise.

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How do you handle tight deadlines and high-pressure situations?

Share your strategies for managing stress and maintaining productivity under pressure. Discuss time management techniques, prioritization of tasks, and how you ensure the team stays focused on key deliverables without compromising quality.

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Visa Inc. operates as a payments technology company worldwide. The company facilitates commerce through the transfer of value and information among consumers, merchants, financial institutions, businesses, strategic partners, and government entiti...

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Full-time, hybrid
DATE POSTED
January 10, 2025

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