Visa is searching for
Data Science Lead.
Company is currently seeking for an individual contributor to Russia Data Science team to support local data products initiative. The key responsibilities of the role will include creating new highly demanding analytical solutions for broad set of consumers (B2B). This role assumes support of existing local data products as second priority.
As a leader of the project you will be accountable for architecturing the design, as well as development and implementation of final product. In this role you will partner with Visa Consulting & Analytics, Business, Finance and Technology teams across the organization to implement solutions to drive business performance.
Data Science team within Visa:Data Science is responsible for blueprinting and delivering projects with the appropriate analytic methodologies and techniques to solve client’s business objectives. The team closely collaborates with other analytic stakeholders to understand the business problem in order to determine the most appropriate analytic approach that provides meaningful results to clients. Responsibilities include delivering projects on time and within scope with an in-depth knowledge of big data and cutting edge data mining techniques as well as the use of predictive, classification and alternate analytic algorithms for modeling and segmentation. These analyses are foundational to corroborate or refute stated hypotheses and are incorporated in the final client-facing solutions. The team is responsible for continuously creating and protecting analytic IP resulting
from project learning.
Global Data Science team is the engine of analytics at Visa; this is a high-performing team of data scientists, data analysts, statisticians, and business analysts from a variety of countries – serving the Asia Pacific, Central Europe, Middle East and Africa geographies.
Visa DS is looking for a hands-on manager, a person that earns trust and respect of the team. The Manager must be results oriented, highly organized, and must, must be focused on delivering innovative analytics work.
This role doesn't involve team management.
Responsibilities:
- Dealing with the partner and clients to build comprehensive development roadmap
- Executing on the analytic plan with appropriate data mining and analytic techniques
- Implementing complex big data algorithms on matching transactional and 3rd party client-centric data
- Conducting transaction data analysis within Hadoop ecosystem
- Improving current matching algorithms with advanced big data technics
- Automating data pipeline using Apache Airflow
- Supporting big data production solutions
- Ensuring constant development and improvement of production big data solutions
- Performing QA on data and deliverables by analysts and own deliverables
- Ensuring project delivery within timelines
- Finding opportunities to create and automate repeatable analyses or build streamlined solutions for internal and external Visa clients
- Collaborating with Visa’s internal functions to fully understand business requirements and desired business outcomes
- Building on team’s analytical skills and business knowledge
Skills:
- Minimum 5 years of big data analysis. That must include automated pipelines development, Hadoop, Spark, Hive, Presto or similar
- Proficiency with DS technologies; experience with Python, Scala, SQL
- End-to-end development skills from business understanding and data preparation to quality assurance of big data solution
- Analytical expertise in applying statistical solutions to business problems (e.g., experience in payments, consumer banking, commercial banking, FMCG retail, consulting, heavy industry)
- Strong in defining and designing analytic approaches to business problems, strong in decomposing heavy business problems into structured and time predictable analytical tasks
- Experience in scaling up ML / big data solutions
- Excellent communication skills in both spoken and written English (upper intermediate plus), Russian fluent speaker
- Nice to have practical experience in building and applying machine learning models (regression, clustering, classification: gradient boosting, random forests, linear models, deep learning etc.); understanding in how do these algorithms work
At least 2 out of 3:
- Degree (masters or PhD would be an advantage) in quantitative field such as statistics, mathematics, operational research, computer science, economics, or engineering or equivalent experience
- Demonstrated resource planning and delivery skills
- Ensure the usage of the correct analytic measures and metrics to solve the business problem; statistical experiments set up and ability to calculate business impact
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