Manager, Data Science and Data Engineering

Bengaluru, India

Visa

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

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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

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 Data Science – Manager (Sr. Data Scientist), 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, new data engineering pipeline development and management - 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 engineers, 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 using data.

Role Requirements and Responsibilities:

In this role, you will be instrumental in a diverse range of projects, varying according to Visa's client needs and specifications. You will collaborate closely with VCA AP regional teams including market data science teams, the hub team in Singapore, and Visa's clients, to address their most pressing business challenges.

As part of the project team, you'll contribute to the design, development, and delivery of data analytics and data engineering solutions, alongside an array of stakeholders. This could involve developing new solutions, automating existing ones, and engaging in the long-term maintenance & delivery of client deliverables.

You'll take on the responsibility of liaising with market data science teams to understand their needs, analyze and develop the requirements. This could comprise building necessary data pipelines, designing local data warehouses/marts, and developing analytical/statistical reports and deliverables. Moreover, you'll cater to different data presentation techniques and automate processes for frequent or recurring deliveries, based on client requirements.

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:
• 5+ years of relevant work experience with a Bachelor’s Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD, OR 8+ years of relevant work experience.


Preferred Qualifications:
• 6 or more years of work experience with a Bachelors Degree or 4 or more years of relevant experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or up to 3 years of relevant experience with a PhD
• 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, MLFlow, 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.

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Tags: Airflow Banking Big Data Clustering Consulting Credit risk Data Analytics Data pipelines E-commerce Engineering Finance Fraud risk Machine Learning MLFlow ML models Open Source PhD Pipelines Power BI Python R Spark SQL Statistics Streaming Tableau

Perks/benefits: Career development Flex hours

Region: Asia/Pacific
Country: India

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