Senior Data Scientist

Selective Global Search; Bengaluru; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Selective Global Search is seeking an experienced data scientist to drive end-to-end ML projects using Python and modern libraries. You will handle data ingestion, feature engineering, model development, and deployment, while collaborating with teams to deliver actionable insights.

The role requires hands-on experience in DL frameworks, NLP, and cloud deployment on Azure or AWS, plus familiarity with Docker, CI/CD, and API development. Strong mentoring skills are a plus.

Qualifications

• Strong expertise in Python and key data science libraries (e.g., pandas, NumPy, scikit-learn, PyTorch/TensorFlow/Keras).
• Proven experience in classical ML algorithms regression, classification, clustering, decision trees, random forests, SVMs, neural networks, etc.
• Solid grounding in statistical analysis and hypothesis testing (DOE, forecasting, segmentation, uncertainty analysis, etc.).
• Hands-on experience with data pre processing, feature engineering, imputation, cleansing, transformation, and data exploration techniques (mean-variance, k-means, nearest neighbor, outlier detection, etc.).
• Strong understanding of machine learning pipeline design, from data ingestion to model evaluation and deployment.
• Experience with deep learning frameworks for solving applied problems (e.g., CNNs, RNNs, Transformers).
• Experience working with NLP.
• Exposure to AI/ML deployment on cloud platforms such as Azure or AWS.
• Working knowledge of Docker, CI/CD pipelines, and API development (Flask/Django).
• Experience developing dashboards or reports in Power BI or similar tools.
• Experience mentoring and providing technical direction to team members.

Responsibilities

• Lead Python-based data science projects end-to-end, from data ingestion to deployment.
• Develop and evaluate ML models using classical and deep learning techniques.
• Perform statistical analysis, hypothesis testing, and data exploration to derive insights.
• Engineer features, clean data, and preprocess datasets for model training.
• Design robust ML pipelines and automate evaluation, deployment, and monitoring.
• Collaborate with cross-functional teams and mentor juniors on best practices.
• Build dashboards/reports to communicate findings and performance.

Skills

Python

Data science libraries

pandas

NumPy

scikit-learn

PyTorch

TensorFlow

Keras

ML algorithms

statistical analysis

DOE

feature engineering

data preprocessing

NLP

Tools

Docker

CI/CD

API development (Flask/Django)

Power BI

Cloud platforms (Azure/AWS)

Job description

Role & responsibilities :

Looking an immediate, serving or 30 days notice period only.

• Strong expertise in Python and key data science libraries (e.g., pandas, NumPy, scikit-learn, PyTorch/TensorFlow/Keras).
• Proven experience in classical ML algorithms regression, classification, clustering, decision trees, random forests, SVMs, neural networks, etc.
• Solid grounding in statistical analysis and hypothesis testing (DOE, forecasting, segmentation, uncertainty analysis, etc.).
• Hands-on experience with data pre processing, feature engineering, imputation, cleansing, transformation, and data exploration techniques (mean-variance, k-means, nearest neighbor, outlier detection, etc.).
• Strong understanding of machine learning pipeline design, from data ingestion to model evaluation and deployment.
• Experience with deep learning frameworks for solving applied problems (e.g., CNNs, RNNs, Transformers).
• Experience working with NLP.
• Exposure to AI/ML deployment on cloud platforms such as Azure or AWS.
• Working knowledge of Docker, CI/CD pipelines, and API development (Flask/Django).
• Experience developing dashboards or reports in Power BI or similar tools.
• Experience mentoring and providing technical direction to team members.