Gen AI Data Scientist
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Job Location:
Monthly Salary:
Posted on:
22 hours ago
Vacancies:
1 Vacancy
Job Summary
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. Youll lead end-to-end model development: data preparation model design with PyTorch or TensorFlow scalable training with distributed engines and production hand-offworking closely with engineers consultants and business stakeholders.
This position requiresa strong foundationin machine learning deep learning predictive modeling and multi-modal AI and provenproficiencyin 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 teammembers;contribute to best practices code reviews and architecture decisions.
Required qualifications
35years hands-on experience building ML or deep learning models usingPyTorchor TensorFlow.
&Python programming skills; experience producing clean well-documented version-controlled code.
Experience with distributed computing engines (e.g. Spark/PySparkDask Ray) for large-scale data processing.
Solid understanding of core ML concepts: supervised/unsupervised learning neural network architectures regularizationevaluationmetrics and model validation.
Experience with model training workflows hyperparameter tuning tools and ML tooling ().
Proven communicationand interpersonalskills and experience working in cross-functional teams.
Preferred (nice-to-have)
Experience with graph databases and graph ML (Neo4j Amazon Neptune) or libraries likePyTorchGeometric.
Background in cybersecurity use cases (threat detection anomalydetection/fraud analytics).
Familiarity with cloud platforms (AWS Azure GCP) and containerization/orchestration (Docker Kubernetes).
Exposure toMLOpspractices: CI/CD for models model monitoring automated retraining.
Advanced degree (MSdegree or higher) in Computer Science Statistics Data ScienceApplied Mathematics computational sciencesor relatedfield.
Preferred Qualifications:
- Bachelors or Masters 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.
Required Experience:
IC
Key Skills
- Laboratory Experience
- Immunoassays
- Machine Learning
- Biochemistry
- Assays
- Research Experience
- Spectroscopy
- Research & Development
- cGMP
- Cell Culture
- Molecular Biology
- Data Analysis Skills
