Staff Data Science (with Credit Risk Modeling)

Bengaluru, India


Das digitale und mobile Zahlungsnetzwerk von Visa steht an der Spitze der neuen Zahlungstechnologien für die neue Zahlung, elektronische und kontaktlose Zahlung, die die Welt des Geldes bilden

View all jobs at Visa

Apply now Apply later

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

Job Description and Responsibilities

Team Summary

Visa Consulting & Analytics (VCA) team is a key part of the Global Solutions organization, a high-performing team of data scientists, data analysts and statisticians helping major organizations adapt and evolve to meet the changes taking place in technology, finance, and commerce, with cutting-edge, creative and advanced analytic solutions.

Visa is looking for Sr. Data Scientist (Manager level), who will be the responsible for leading data science engagements with our partners and supporting end-to-end delivery. 

What a Data Science – Manager (Sr. Data Scientist) does at Visa:

The Data Science – Manager (Sr. Data Scientist) will be a member of VCA Data Science team in Asia Pacific. The position will be based in Visa’s Bangalore office.

The individual will be accountable for supporting and driving the design, development and implementation of analytics-driven strategies as well as high-impact solutions for Visa clients. He/she will bring in deep expertise from banking and payments with a strong background in data science to solve complex problems and unlock business value.

  • Manage and deliver analytics projects from conception to completion with actionable insights and recommendations

  • Define detailed scope and methodology, design and create solutions, and execute on the framework leveraging appropriate tools and techniques

  • Actively seek out opportunities to innovate by using VisaNet, non-traditional data and new modelling techniques fit for purpose to the needs of our clients

  • Enhance existing analytic techniques by promoting new methodology and best practices in analytics

  • Develop metrics and use dashboards to quantify current state and to monitor progress across markets and segments using consistent definitions

  • Act as data science advocate within our partners, advising and coaching analytical teams and sharing best practices and case studies.

  • Collaborate with cross-functional teams to build and automate re-usable and scalable solutions

Why this is important to Visa

As payments consulting arm of Visa, VCA is growing a team of highly specialized experts who can provide best-in-class payment expertise and data-driven strategies to clients. We are building a high-performing team of data scientists, data analysts and statisticians helping major organizations adapt and evolve to meet the changes taking place in technology, finance, and commerce, with cutting-edge, creative and advanced analytic solutions. The purpose of the team is to help Visa’s clients grow their business and solve problems by providing consulting services through the use of data.

Projects you will be a part of:

The nature of projects this role will play a key role in vary. This would include collaborating with Visa Consumer Solution team, Open data solution, Merchant team, to solve their most strategic business problems. Here are some sample problems

  • Benefit measurement: how to evaluate if a campaign promotion is making positive ROI? Does it generate positive impacts to the campaign participating merchants? How about the overall impacts to Visa? How to identify proper test and control group so that make more scientific inference? What do you recommend to program managers to optimize the offerings? How to collaborate with different stakeholders to commercialize the benefit platform?

  • Loyalty: how to work with stakeholders to improve the existing loyalty platform by leveraging various AI models?

  • Buy-Now-Pay-Later:  what does the typical BNPL adopter look like?  Who has the higher chance to take the instalment offers, on which transaction(s)?

  • Open data:  how to support stakeholders for potential joint development with 3rd party

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.


• 7+ years’ experience plus a Bachelor’s degree in computer science, information science, mathematics, or similar/related streams. Graduate Master’s degree is a plus.
• Hands-on in developing machine learning solutions, delivering end-to-end data science projects, scaling up data solutions (Must have). Familiar with data handling techniques including cleaning, wrangling, feature development and extraction, feature selection, etc is required. Familiar with typical machine learning models such as Linear & Logistic Regression, Decision Trees, Random Forests, Markov Chains, Support Vector Machines, Neural Networks, Clustering, etc.
• Experience with Big Data technologies, data engineering tools is a must (Must have). Experience of working with complex, high volume, multi-dimensional data, as well as machine learning models based on unstructured, structured, and streaming datasets. Proficient in big data aggregation using Hive, Spark, SQL, R/Python, and other related packages. Experience with data engineering (pipeline creation and automation) tools like Airflow, MFlow, etc., will also be a plus.
• Experience in Credit Risk or Fraud Risk analytics, Marketing Analytics will be a big plus.
• Experience with visualization, reporting, BI tools, such as advanced user of PPT, Power BI, Tableau, MicroStrategy, open-source tool, or similar tools is a plus.
• Outstanding problem-solving skills, with demonstrated ability to think creatively and strategically
• Experience in planning, organizing, and managing multiple analytic projects with diverse cross-functional stakeholders (Must have)
• Strong internal team and external client stakeholder management with a collaborative, diplomatic, and flexible style, able to work effectively in a matrixed organization
• Exhibit intellectual curiosity and strive to continually learn, self-motivated and results oriented individual with the ability to handle numerous projects
• Banking /Payment /e-Commerce industry experiences are not desired but preferred

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.

Apply now Apply later
  • Share this job via
  • or

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Job stats:  2  0  0
Category: Leadership Jobs

Tags: Airflow Banking Big Data Clustering Computer Science Consulting Credit risk E-commerce Engineering Finance Fraud risk Machine Learning Mathematics ML models Open Source Power BI Python R Spark SQL Streaming Tableau

Perks/benefits: Career development Flex hours

Region: Asia/Pacific
Country: India

More jobs like this

Explore more AI, ML, Data Science career opportunities

Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.