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Senior data science

1 month ago

Bangalore, India Visa Full time

Job Description .

What a Data Science – Sr.

Data Scientist does at Visa: The Data Science – 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 Visa Net, 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.

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.

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 Ph D, 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 Ph D • 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, Micro Strategy, 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.