Data Scientist

Overview

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Preferred to be in onshore, if not offshore India but candidate should be based out of Bangalore

Interview Process: Single round, Face-to-Face only

Experience: 5–6 years

Profile Expectation: Strong hands-on, hardcore development-oriented candidates

Required Skills:

Strong proficiency in Python (Pandas, NumPy, Scikit-learn)

Strong SQL skills for data extraction and analysis

Hands-on experience in Machine Learning (regression, classification, clustering)

Solid understanding of statistics and probability

Experience in data cleaning, feature engineering, and model evaluation

Knowledge of time series analysis and forecasting

Tools & Platforms:

Python libraries: Scikit-learn, TensorFlow / PyTorch (preferred)

Data visualization: Power BI, Tableau, Matplotlib, Seaborn

Big data exposure: Spark / PySpark (good to have)

Version control: Git / GitHub

Cloud exposure: AWS, Azure, or GCP

Data platforms: Snowflake / BigQuery / Redshift (preferred)

Understanding of ETL and data pipelines

Business & Domain Exposure:

Ability to convert business problems into data-driven solutions

Experience working with large, real-world datasets

Strong analytical, communication, and stakeholder management skills

Domain exposure to Banking, Insurance, Retail, or Telecom is a plus

Experience in risk modeling, customer analytics, or fraud detection is desirable

Awareness of data privacy and compliance standards (POPIA knowledge is an advantage)