Data Scientist

Role Overview : Data Scientist Location : Remote / Indore / Mumbai / Chennai / Gurugram

Experience : Min 5 Years

Work Mode : Remote

Notice Period : Max. 30 Days (45 for Notice Serving)

Interview Process : 2 Rounds

Interview Mode : Virtual Face-to-Face

Interview Timeline : 1 Week

Industry : Must be from a BPO / KPO / Shared Services or Healthcare Org.

Key Responsibilities :

AI / ML Development & Research

Design, develop, and deploy advanced machine learning and deep learning models to solve complex business problems.

Implement and optimize Large Language Models (LLMs) and Generative AI solutions for real-world applications.

Build agent-based AI systems with autonomous decision-making capabilities.

Conduct cutting-edge research on emerging AI technologies and explore their practical applications.

Perform model evaluation, validation, and continuous optimization to ensure high performance.

Cloud Infrastructure & Full-Stack Development :

Architect and implement scalable, cloud-native ML / AI solutions using AWS, Azure, or GCP.

Develop full-stack applications that seamlessly integrate AI models with modern web technologies.

Build and maintain robust ML pipelines using cloud services (e.g., SageMaker, ML Engine).

Implement CI / CD pipelines to streamline ML model deployment and monitoring processes.

Design and optimize cloud infrastructure to support high-performance computing workloads.

Data Engineering & Database Management

Design and implement data pipelines to enable large-scale data processing and real-time analytics.

Work with both SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, Cassandra) to manage structured and unstructured data.

Optimize database performance to support machine learning workloads and real-time applications.

Implement robust data governance frameworks and ensure data quality assurance practices.

Manage and process streaming data to enable real-time decision-making.

Leadership & Collaboration

Mentor junior data scientists and assist in technical decision-making to drive innovation.

Collaborate with cross-functional teams, including product, engineering, and business stakeholders, to develop solutions that align with organizational goals.

Present findings and insights to both technical and non-technical audiences in a clear and actionable manner.

Lead proof-of-concept projects and innovation initiatives to push the boundaries of AI / ML applications.

Required Qualifications :

Education & Experience

Master’s or PhD in Computer Science, Data Science, Statistics, Mathematics, or a related field.

5+ years of hands-on experience in data science and machine learning, with a focus on real-world applications.

3+ years of experience working with deep learning frameworks and neural networks.

2+ years of experience with cloud platforms and full-stack development.

Technical Skills - Core AI / ML

Machine Learning : Proficient in Scikit-learn, XGBoost, LightGBM, and advanced ML algorithms.

Deep Learning : Expertise in TensorFlow, PyTorch, Keras, CNNs, RNNs, LSTMs, and Transformers.

Large Language Models : Experience with GPT, BERT, T5, fine-tuning, and prompt engineering.

Generative AI : Hands-on experience with Stable Diffusion, DALL-E, text-to-image, and text generation models.

Agentic AI : Knowledge of multi-agent systems, reinforcement learning, and autonomous agents.

Technical Skills - Development & Infrastructure

Programming : Expertise in Python, with proficiency in R, Java / Scala, JavaScript / TypeScript.

Cloud Platforms : Proficient with AWS (SageMaker, EC2, S3, Lambda), Azure ML, or Google Cloud AI.

Databases : Proficiency with SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Cassandra, DynamoDB).

Full-Stack Development : Experience with React / Vue.js, Node.js, FastAPI, Flask, Docker, Kubernetes.

MLOps : Experience with MLflow, Kubeflow, model versioning, and A / B testing frameworks.

Big Data : Expertise in Spark, Hadoop, Kafka, and streaming data processing.

Non Negotiables :

Cloud Infrastructure - ML / AI solutions on AWS, Azure, or GCP

Build and maintain ML pipelines using cloud services (SageMaker, ML Engine, etc.)

Implement CI / CD pipelines for ML model deployment and monitoring

Work with both SQL and NoSQL databases (PostgreSQL, MongoDB, Cassandra, etc.)

Machine Learning : Scikit-learn

Deep Learning : TensorFlow

Programming : Python (expert), R, Java / Scala, JavaScript / TypeScript

Cloud Platforms : AWS (SageMaker, EC2, S3, Lambda)

Vector databases and embeddings (Pinecone, Weaviate, Chroma)

Knowledge of LangChain, LlamaIndex, or similar LLM frameworks.

Industry : Must be a BPO or Healthcare Org.