Job Description:
Job Title-Data Scientist (Client Insights).
Reporting To-Analytics Lead.
Position Purpose:-Solution and deliver analytics offerings for the bank to drive revenue or enable cost optimization. Build models,
move them to production and maintain/ enhance on an ongoing basis in production. Become an analytics
consultant and evangelist within the bank finding analytical solutions to business problems.
Position Responsibilities:-1.Work closely with the data warehouse team/other business teams to obtain relevant data for
implementation. Be comfortable working with structured / unstructured data sources and be conversant
to perform secondary research to explore third party data sources to enrich existing data.
2.Support the overall digital acquisition strategy by focusing on segmenting/ predicting response rates for
leads which are a pre-requisite for improving response rates.
3.Create/supervise building of models around channel migration ,cross sell , upsell and support the overall
customer engagement strategy.
4.Support the implementation of various technology(recommendation engine, campaign management
solution, CRM) /data enablers(Creation of data sets ,mart etc) for the analytics practice within the bank.
5.Implementation of specific use cases on big data platforms .
Qualifications and Experience Requirement:-Graduate (B.E /B.Sc Stats/M.Sc Stats or equivalent).
Experience:-? 1-3 years in the analytics space
? Managed diverse stakeholders from various teams, in complex
environments
? Grasp of basic Supervised/ Unsupervised ML algorithms and a
demonstrated ability to learn quickly
? Thorough understanding of banking domain would be a plus point
? Experience in working with SQL & R/other similar statistical
programming languages .Knowledge of other statistical
programming languages like Python will be an added advantage.
Skill:-Team player, detail oriented,
self-motivated individual.
Attribute:-Candidate should have a strong understanding of analytical modeling
techniques and statistical concepts that are relevant to the application and
evaluation of models.
