Data Science Engineer
Location: India
Job Type: Full Time
Status: Active
Posted: 2026-04-13 07:19:00
Job Description
Position Description:
We’re looking for a Senior Data Scientist with strong analytical thinking, deep technical expertise, and a proven ability to apply machine learning to solve real-world problems. The candidate should have 4+ years of high-quality proven experience in AI/ML working. You’ll work with cross-functional teams to design, develop, and deploy scalable AI/ML solutions, including Generative AI, predictive modeling, and recommendation systems.
Education Qualification:
Bachelor's degree in Computer Science or related field or higher with minimum 6 years of relevant experience.
Roles and Responsibilities:
- Design, build, and validate machine learning and deep learning models, ensuring robustness, scalability, and explainability.
- Apply strong statistical foundations to analyze large datasets and derive actionable insights.
- Lead the development and evaluation of models using modern ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow).
- Drive the adoption of Generative AI and LLM-based solutions, ensuring model alignment, prompt engineering, and ethical AI practices.
- Collaborate with data engineers, product teams, and business stakeholders to transform
- business problems into technical solutions.
- Contribute to code reviews, model documentation, and mentorship of junior data scientists.
- Stay abreast of the latest research and translate cutting-edge methods into production.
Required Qualifications
- Bachelor’s or master’s degree in computer science, Statistics, Applied Mathematics, or a related field.
- Statistical and Mathematical Rigor: Strong grasp of descriptive and inferential statistics (hypothesis testing, A/B testing, regression, probability theory).
- Understanding of bias-variance trade-off, regularization, overfitting, and model validation techniques.
- Machine Learning & Deep Learning: Hands-on experience with a range of algorithms: decision trees, ensemble models, SVMs, neural networks, clustering, and NLP techniques.
- Proficiency in deep learning architectures such as CNNs, RNNs, Transformers, and LSTMs.
- Generative AI & LLMs: Conceptual and practical knowledge of Large Language Models (e.g., GPT, BERT, LLaMA), fine-tuning, embeddings, and prompt engineering.
- Tooling & Deployment: Experience with cloud platforms (AWS, GCP, Azure), ML pipelines (MLflow, Airflow, Kubeflow), and containerization (Docker, Kubernetes).
- Version control (Git) and collaborative development practices.
- Familiarity with generative modeling approaches (e.g., VAEs, GANs, diffusion models) is a strong plus.
- Programming & Problem Solving: Advanced proficiency in Python with the ability to write clean, modular, and testable code.
- Experience with libraries such as NumPy, pandas, matplotlib, scikit-learn, PyTorch, TensorFlow, and HuggingFace.
- Strong problem-solving skills with the ability to tackle coding challenges independently and efficiently.
Skills
Deep Learning (PyTorch/TensorFlow), Generative AI (LLMs), Machine Learning, Python, Statistics
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