Gen AI Data Scientist

DataPune

Posted On

12 Mar 2026

End Date

30 Jun 2026

Required Experience

6 - 9 Years

Basic Section

Grade

Role

Technical Lead

Employment Type

Full Time

Employee Category

Organisational

Group Company

NewVision

Company Name

New Vision Softcom & Consultancy Pvt. Ltd

Function

Business Units (BU)

Department/Practice

Data

Organization Unit

Data Science

Region

APAC

Country

India

Base Office Location

Pune

Working Model

Hybrid

Weekly Off

Pune Office Standard

State

Maharashtra

Skills

Skill

DATA SCIENCE - AI

MACHINE LEARNING

PYTHON

COMPUTRE VISION NLP

ML FRAMEWORKS, PYTORCH

DEEP LEARNING

PREDICTION MODELLING-ADVANCED DATA MINING AND VISU

.NET

PYTHON PROGRAMMING EXPERTISE

NEO4J

Highest Education

GRADUATION/EQUIVALENT COURSE

CERTIFICATION

No data available

Working Language

ENGLISH

Job Description

Data Scientist – Gen AI, ML, Deep Learning, NLP & Graph Intelligence

Experience: 6-9 Years

Location: Pune

Employment Type: Full-time

Role Overview:

We are seeking a highly experienced and forward-thinking Senior Data Scientist to lead cutting-edge initiatives in Generative AI, Machine Learning, and Graph Intelligence. This role demands deep expertise in Neo4j, AWS Neptune, NLP, and LLM frameworks, with a strong foundation in predictive analytics and solution architecture. You will be instrumental in designing scalable, intelligent systems that transform data into actionable insights.

Key Responsibilities:

We are seeking an experienced Data Scientist for Cyber Analytics & AI team to design, build, and deploy machine learning and deep learning solutions for client engagements. You’ll lead end-to-end model development: data preparation, model design with PyTorch or TensorFlow, scalable training with distributed engines and production hand-off—working closely with engineers, consultants, and business stakeholders.

This position requires a strong foundation in machine learning, deep learning, predictive modeling, and multi-modal AI and proven proficiency in Python and model deep learning frameworks.

• Design, develop, and validate ML/DL models using PyTorch or TensorFlow for real business problems.
• Implement production-ready code in Python and collaborate with engineering teams for deployment.
• Process and transform large datasets using distributed computing frameworks (Dask/Ray).
• Lead model training, hyperparameter tuning, experiment tracking, and performance evaluation.
• Build reusable pipelines and components for feature engineering, training, and inference.
• Translate business use cases into technical solutions and present model findings to non-technical stakeholders.
• Ensure model reliability, monitoring, and compliance with governance and security requirements.
• Mentor junior team members; contribute to best practices, code reviews, and architecture decisions.

Required qualifications

• 3–5 years hands-on experience building ML or deep learning models using PyTorch or TensorFlow.
• Strong .Net & Python programming skills; experience producing clean, well-documented, version-controlled code.
• Experience with distributed computing engines (e.g., Spark/PySpark, Dask, Ray) for large-scale data processing.
• Solid understanding of core ML concepts: supervised/unsupervised learning, neural network architectures, regularization, evaluation metrics, and model validation.
• Experience with model training workflows, hyperparameter tuning tools, and ML tooling (e.g., MLflow, TensorBoard).
• Proven communication and interpersonal skills and experience working in cross-functional teams.

Preferred (nice-to-have)

• Experience with graph databases and graph ML (Neo4j, Amazon Neptune) or libraries like PyTorch Geometric.
• Background in cybersecurity use cases (threat detection, anomaly detection/fraud analytics).
• Familiarity with cloud platforms (AWS, Azure, GCP) and containerization/orchestration (Docker, Kubernetes).
• Exposure to MLOps practices: CI/CD for models, model monitoring, automated retraining.
• Advanced degree (MS degree or higher) in Computer Science, Statistics, Data Science, Applied Mathematics, computational sciences, or related field.

Preferred Qualifications

• Bachelor's or Master’s or Ph.D. in Computer Science, Data Science, AI, or a related field.
• Experience with graph neural networks, semantic search, or knowledge graph reasoning.
• Exposure to ethical AI, data privacy, and responsible AI practices.
• Contributions to open-source AI/ML projects or research publications.