Data Scientist

Job Description

JOB DESCRIPTION Job Title: Data Scientist Experience: 5-10 years Location: Pune, India Role Definition: Data Scientists focus on researching and developing AI algorithms and models. In this role, you will analyze data, build predictive models, and apply machine-learning techniques to solve complex problems. Key Responsibilities: Research and develop AI algorithms and predictive models. Analyze data to extract actionable insights. Build, test, and deploy machine learning and deep learning models. Manage end-to-end AI solution delivery, from data mining and cleaning to deployment. Collaborate with cross-functional teams to integrate AI solutions into business processes. Ensure effective monitoring and maintenance of data pipelines and model performance. Required Skills: Proficient: Languages/Frameworks: Fast API, Azure UI Search API (React) Databases and ETL: Cosmos DB (API for MongoDB), Data Factory, and Data Bricks Programming: Proficiency in Python and R Cloud: Azure Cloud Basics (Azure DevOps) Version Control & CI/CD: Gitlab Pipeline Deployment: Ansible and REX (Rex Deployment) Data Science: Prompt Engineering, Modern Testing, and data mining/cleaning Machine Learning: Supervised/unsupervised learning, NLP techniques, and familiarity with deep learning techniques (RNN, transformers) End-to-End Delivery: AI integration, deployment, and model deployment processes Frameworks & Operations: AI frameworks (PyTorch), MLOps frameworks, and data pipeline monitoring Expert (in addition to the proficient skills): Languages/Frameworks: Expertise in Azure Open AI Data Science: Proficiency with Open AI GPT Family of models (4o/4/3), embeddings, and vector search Databases and ETL: Experience with Azure Storage Account Machine Learning: Expertise in a broad range of machine learning algorithms (supervised, unsupervised, reinforcement learning) Deep Learning: Proficiency in deep learning frameworks (TensorFlow, PyTorch) Mathematics: Strong mathematical foundation in linear algebra, calculus, probability, and statistics Research: Solid research methodology and experimental design skills Data Analysis: Proficiency in data analysis tools (Pandas, NumPy, SQL) Statistics: Strong statistical and probabilistic modeling skills Data Visualization: Experience with tools like Matplotlib, Seaborn, or Tableau Big Data: Knowledge of big data technologies such as Spark and Hive Analytics: Experience with AI-driven analytics and decision-making systems