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About the role
Role Overview : We are seeking a Senior Data Scientist with strong analytical thinking, deep technical expertise, and proven experience in building and deploying AI/ML and Generative AI solutions. The ideal candidate will work closely with cross-functional teams to translate complex business problems into scalable machine learning solutions, including predictive models, recommendation systems, NLP, and LLM-based applications. Key Responsibilities : - Design, build, validate, and deploy machine learning and deep learning models ensuring scalability, robustness, and explainability - Apply strong statistical methods to analyze large datasets and generate actionable insights - Develop and evaluate models using frameworks such as scikit-learn, PyTorch, and TensorFlow - Lead adoption of Generative AI and LLM-based solutions, including prompt engineering and model alignment - Collaborate with data engineers, product teams, and business stakeholders to convert business use cases into technical solutions - Participate in code reviews, model documentation, and mentor junior team members - Stay updated with the latest research and apply cutting-edge AI/ML techniques in production environments Required Skills & Qualifications : Statistical & Mathematical Foundations : - Strong understanding of descriptive and inferential statistics - Experience with hypothesis testing, A/B testing, regression, probability theory - Knowledge of bias-variance trade-off, regularization, overfitting, and model validation Machine Learning & Deep Learning : - Hands-on experience with algorithms such as decision trees, ensemble models, SVMs, clustering, and NLP techniques - Proficiency in deep learning architectures including CNNs, RNNs, LSTMs, and Transformers Generative AI & LLMs : - Practical knowledge of Large Language Models (GPT, BERT, LLaMA) - Experience with fine-tuning, embeddings, prompt engineering, RAG, and Agentic AI - Familiarity with VAEs, GANs, diffusion models is a plus Programming & Tools : - Advanced proficiency in Python - Strong experience with NumPy, pandas, scikit-learn, PyTorch, TensorFlow, HuggingFace - Good problem-solving and clean, modular coding practices MLOps & Deployment : - Experience with cloud platforms: AWS / Azure / GCP - Knowledge of ML pipelines and orchestration tools: MLflow, Airflow, Kubeflow - Experience with Docker, Kubernetes - Strong understanding of Git and collaborative development workflows Role Overview : We are seeking a Senior Data Scientist with strong analytical thinking, deep technical expertise, and proven experience in building and deploying AI/ML and Generative AI solutions. The ideal candidate will work closely with cross-functional teams to translate complex business problems into scalable machine learning solutions, including predictive models, recommendation systems, NLP, and LLM-based applications. Key Responsibilities : - Design, build, validate, and deploy machine learning and deep learning models ensuring scalability, robustness, and explainability - Apply strong statistical methods to analyze large datasets and generate actionable insights - Develop and evaluate models using frameworks such as scikit-learn, PyTorch, and TensorFlow - Lead adoption of Generative AI and LLM-based solutions, including prompt engineering and model alignment - Collaborate with data engineers, product teams, and business stakeholders to convert business use cases into technical solutions - Participate in code reviews, model documentation, and mentor junior team members - Stay updated with the latest research and apply cutting-edge AI/ML techniques in production environments Required Skills & Qualifications : Statistical & Mathematical Foundations : - Strong understanding of descriptive and inferential statistics - Experience with hypothesis testing, A/B testing, regression, probability theory - Knowledge of bias-variance trade-off, regularization, overfitting, and model validation Machine Learning & Deep Learning : - Hands-on experience with algorithms such as decision trees, ensemble models, SVMs, clustering, and NLP techniques - Proficiency in deep learning architectures including CNNs, RNNs, LSTMs, and Transformers Generative AI & LLMs : - Practical knowledge of Large Language Models (GPT, BERT, LLaMA) - Experience with fine-tuning, embeddings, prompt engineering, RAG, and Agentic AI - Familiarity with VAEs, GANs, diffusion models is a plus Programming & Tools : - Advanced proficiency in Python - Strong experience with NumPy, pandas, scikit-learn, PyTorch, TensorFlow, HuggingFace - Good problem-solving and clean, modular coding practices MLOps & Deployment : - Experience with cloud platforms: AWS / Azure / GCP - Knowledge of ML pipelines and orchestration tools: MLflow, Airflow, Kubeflow - Experience with Docker, Kubernetes - Strong understanding of Git and collaborative development workflows