Data Scientist - Data Wrangling
Société Générale · Bengaluru
- Experience3–4 yrs
- SalaryNot disclosed
- Work modeonsite
- Posted29 Sept 2026
About Société Générale
Société Générale is hiring in Bengaluru in financial services. This role looks for around 3+ years of experience.
Skills
- SAS
- Python
- Data wrangling
- IRBA/IFRS9 models
- SQL
The role
A data scientist at a financial services company transforms and analyzes datasets using SAS, Python, and data wrangling, applying risk and finance models to produce auditable insights. Dataiku and SQL support automated, optimized data workflows for global banking audiences.
Full job description
Responsibilities
Familiarizing with data, to conceptualize its use. Transform data sets, quantitative and qualitative analysis into desired
data requirements
Reviewing the code to spot any potential issues, which might have probability of having cascading future effects like
identify trends and patterns in the data or identify anomalies such as missing or incomplete values etc.
Code automation & optimization and replacing referential user data with tech managed data platforms
Create robust and auditable documentation
Understand the data's audience and purpose and liaising with the data consumers, for mutual use of data to reduce time
to market
Recommending strategy through testing or exploratory data analysis
Profile required
Hands on working experience in SAS/ Python (3+ years)
Should be familiar with data wrangling concepts like, cleaning, organizing, and transforming raw data into the desired
format, IRBA/IFRS9 models knowledge
Experience working with Global Banks in their Risk & finance function
Basic knowledge of programing languages like SQL & Python
Dataiku knowledge would be an added advantage
Should have good communication skill
Business insight
.
Diversity and Inclusion
We are an equal opportunities employer and we are proud to make diversity a strength for our company. Societe Generale is committed to recognizing and promoting all talents , regardless of their beliefs, age, disability, parental status, ethnic origin, nationality, gender identity, sexual orientation, membership of a political, religious, trade union or minority organisation, or any other characteristic that could be subject to discrimination.