RBL Bank | Hiring For Data Scientist - Airoli

1. 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

Qualifications

• Essential: Graduate (B.E / B.Sc Stats / M.Sc Stats or equivalent)

Experience

• Essential:
• 3 plus 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

Skills

Skill Attribute

• Team player, detail oriented, self-motivated individual
• Candidate should have a strong understanding of analytical modeling techniques and statistical concepts that are relevant to the application and evaluation of models