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

The position will be based in Visa’s Bangalore office. We are looking for an individual with deep expertise in building & operationalization of data science solutions based on business needs, using VISA’s big data sets and in certain cases in conjunction with our clients’ data. The candidate is expected to have hands on experience with associated technologies and ability to collaborate across teams and functions to deliver value to VISA and our clients. 

The successful candidate will have opportunities to work on huge varieties of problems across Marketing Analytics, Credit Risk, Open banking/ Open data, etc. S/he must have a highly analytical bent of mind and requisite skills to independently analyze and interpret data insights.

We are looking for a talented, technical, proactive, energetic, and passionate person who embraces challenges and is a proven problem solver.

 Principal Responsibilities

• Partner with teams across the organization including consultants, engineering, and data scientists to address prioritized business problems
• Work as part of the project team to understand business requirements, support data collection, cleansing, preparation, feature engineering, model build, evaluation, training, and deployment adhering to project scope and timelines.
• Define detailed scope and methodology, design and create solutions, and execute leveraging appropriate tools and techniques
• Support development of a robust system for measuring and optimizing the quality of deployed algorithms and models.
• Monitor AI models in production to evaluate performance, model drift, and decay.
• 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
• Act as data science advocate within our partners, advising and coaching analytical teams and sharing best practices and case studies.
• Identify, design, and implement internal process improvements to provide greater scalability to our existing client solutions
• Work with data science and data engineering partners in the region and globally to adopt standards and guidelines
• Make sure that the legal/compliance/security related requirements are fully adhered to.

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

Minimum of bachelor’s degree or equivalent. Masters is preferred
Qualification in Data Science/Computer Science from reputed institutes. 
Total 4+ years of experience of which over 3 years being a data scientist or analytics consultant
Hands-on experience in handling end to end data engineering and data analytics tasks. Should have knowledge in developing machine learning models, scaling data solutions, and delivering end-to-end data science projects. Preferably candidates should have hands on in data engineering, data science work experiences OR candidates should have BI, reporting, analytics work experiences.
Experience with big data technologies, data engineering tools is a must. Experience with complex, high volume, multi-dimensional data, as well as machine learning models based on unstructured, structured, and streaming datasets.
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.
Proficient in big data aggregation using Hive, Spark, SQL, R/Python, and familiar with typical deep learning toolkits and packages
Experience with visualization and reporting tools, such as Power BI, Tableau, MicroStrategy, open-source tool, or similar will be a plus. Experience with data engineering (pipeline creation and automation) tools like Airflow, Hue, etc will also be a plus.
Exhibit intellectual curiosity and strive to continually learn, self-motivated and results oriented individual with the ability to handle numerous projects
Ability to learn new tools and paradigms as data science continues to evolve at Visa and elsewhere.
Appreciation of Payments and Banking domain will be a plus
Experience in Marketing Analytics, Credit Risk or Fraud Risk analytics will be a plus
Good communication and presentation skills with ability to interact with different cross-functional team members at varying level
Understanding of credit bureaus and non-traditional data providers will be a plus
Technical Expertise

Experience in writing and optimizing efficient SQL queries and Python/PySpark for data science
Expertise in dashboard and report development using tools such as Tableau/Power BI/Micro Strategy 
Good understanding of Agile way of working, tools such as JIRA and practical experience of working in Agile teams.
Experience in deployment, operationalization of Machine Learning models using MLOps techniques
Working knowledge of Hadoop ecosystem and associated technologies, e.g., Hive, Apache Spark, MLlib, GraphX, sci-kit, and Pandas
Experience with Apache Airflow will be an added advantage
Understanding of best-in-class software engineering practices such as DevOps, CI/CD, and job automation will be a plus   
Experience with data APIs, containerized deployments will be an added advantage  
Experience of cloud-based data science platforms will be an added advantage
Business and Leadership competencies

Results-oriented with strong problem-solving skills and demonstrated intellectual and analytical rigor
Good business acumen with a track record in solving business problems through data-driven quantitative methodologies. Experience in payment, retail banking, or retail merchant industries is preferred
Team oriented, collaborative, diplomatic, and flexible
Detail oriented to ensure highest level of quality/rigor in reports and data analysis
Proven skills in translating analytics output to actionable recommendations and delivery
Experience in presenting ideas and analysis to stakeholders whilst tailoring data-driven results to various audience levels
Exhibits intellectual curiosity and a desire for continuous learning
Demonstrates integrity, maturity, and a constructive approach to business challenges
Role model for the organization and implementing core Visa Values
Respect for the Individuals at all levels in the workplace
Strive for Excellence and extraordinary results
Use sound insights and judgments to make informed decisions in line with business strategy and needs
Ability to influence senior management within and outside Analytics groups
Ability to successfully persuade/influence internal stakeholders for building best-in-class solutions

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.