Associate Data Scientist

Birlasoft ( India ) Limited; Hyderabad, Bengaluru, Pune District, Dadri; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Birlasoft ( India ) Limited is seeking an Associate Data Scientist to join our analytics team in Hyderabad/Bangalore/Pune/Noida with hybrid work. You will design, develop, and deploy AI/ML models and build scalable analytics solutions to solve real business problems.

You will work with data engineers, BI stakeholders, and product owners to operationalize ML in production, implement MLOps, and stay abreast of GenAI advances to drive data-driven decisions across the organization.

Qualifications

• Strong Python and ML model development background.
• Experience with MLOps and CI/CD pipelines.
• Experience with large-scale data analytics and distributed computing.

Responsibilities

• Design, develop, and deploy ML/AI models for real-world business problems.
• Build end-to-end ML pipelines, including data ingestion, feature engineering, model training, validation, and deployment.
• Develop and implement MLOps frameworks for CI/CD, monitoring, and model governance.
• Work closely with data engineering teams to ensure robust and scalable data pipelines.
• Conduct exploratory data analysis (EDA) and hypothesis testing to support data-driven decision‑making.
• Optimize model performance through hyperparameter tuning and advanced techniques.
• Deploy and monitor models in production environments ensuring performance, reliability, and scalability.
• Collaborate with cross‑functional teams including business stakeholders, architects, and product owners.
• Stay updated with the latest advancements in AI/ML, GenAI, and data science tools and frameworks.

Skills

Python

NumPy

Pandas

Scikit-learn

TensorFlow

PyTorch

ML algorithms

Statistical analysis

Hypothesis testing

Regression

Classification

Clustering

Forecasting models

CI/CD pipelines

Model versioning

Monitoring

Deployment

SQL

AWS

Azure

GCP

Tools

Databricks Mosaic AI

Snowflake Cortex

Docker

Kubernetes

Job description

Associate Data Scientist

Area(s) of responsibility

Location: Hyderabad / Bangalore / Pune / Noida (Hybrid)

Experience: 5–12 Years

Employment Type: Full-Time

Role Overview

We are seeking a highly skilled Data Scientist with strong expertise in Artificial Intelligence (AI), Machine Learning (ML), and MLOps. The ideal candidate will be responsible for building scalable predictive models, driving advanced analytics, and operationalizing ML models in production environments. This role requires a deep understanding of statistical modeling, predictive analytics, and Python-based data ecosystems, with exposure to modern platforms such as Databricks Mosaic AI and Snowflake Cortex being an added advantage.

Key Responsibilities

• Design, develop, and deploy machine learning and AI models for real-world business problems.
• Perform advanced statistical analysis and build predictive models to derive actionable insights.
• Develop and implement end-to-end ML pipelines, including data ingestion, feature engineering, model training, validation, and deployment.
• Build and manage MLOps frameworks for continuous integration, delivery, monitoring, and model governance.
• Work closely with data engineering teams to ensure robust and scalable data pipelines.
• Conduct exploratory data analysis (EDA) and hypothesis testing to support data-driven decision‑making.
• Optimize model performance through hyperparameter tuning and advanced techniques.
• Deploy and monitor models in production environments ensuring performance, reliability, and scalability.
• Collaborate with cross‑functional teams including business stakeholders, architects, and product owners.
• Stay updated with the latest advancements in AI/ML, GenAI, and data science tools and frameworks.

Required Skills & Qualifications

• Strong programming expertise in Python (NumPy, Pandas, Scikit‑learn, TensorFlow/PyTorch).
• Hands‑on experience in Machine Learning & AI algorithms (supervised, unsupervised, deep learning).
• Expertise in statistical analysis, hypothesis testing, regression, classification, clustering, and forecasting models.
• Experience with predictive modeling and advanced analytics techniques.
• Solid understanding of MLOps practices including CI/CD pipelines, model versioning, monitoring, and deployment.
• Experience working with large‑scale datasets and distributed computing frameworks.
• Strong knowledge of SQL and data manipulation techniques.
• Familiarity with cloud platforms such as AWS, Azure, or GCP.

Good to Have

• Exposure to Databricks (Mosaic AI, MLflow, Delta Lake).
• Experience with Snowflake Cortex / Snowflake ML capabilities.
• Understanding of Generative AI / LLM‑based applications.
• Experience in model explainability, fairness, and governance frameworks.
• Knowledge of containerization tools like Docker and orchestration tools like Kubernetes.