We are seeking a skilled and business-oriented Data Scientist to design,develop, and deploy AI/ML solutions that solve real-world business problems.The ideal candidate will have hands-on experience in machine learning modeldevelopment, analytics, dashboarding, and emerging GenAI capabilities, alongwith the ability to collaborate effectively with cross-functional stakeholders.The role requires a balance of technical expertise, problem-solving ability,and communication skills to deliver scalable and impactful AI-driven solutions.
KeyResponsibilities
- ML/AI SolutionDevelopment Develop, train, evaluate, and deploy machine learning and AImodels for business use cases including prediction, optimization,automation, and analytics.
- GenAI & LLMApplications Work on Generative AI use cases involving LLMs, promptengineering, RAG-based solutions, AI copilots, and workflow automations
- DataAnalysis & Visualization Perform exploratory data analysis, generateactionable insights, and create dashboards/reports using visualizationtools to support business decision-making
- End-to-EndModel Lifecycle Manage the ML lifecycle including data preparation,feature engineering, model development, validation, deployment, andmonitoring
- StakeholderCollaboration Partner with business stakeholders, product teams, andtechnology teams to understand requirements and translate them intoscalable analytical and AI solutions
- MLOps& Deployment Support model deployment and monitoring using MLOpspractices and tools. Collaborate with engineering teams for integrationinto production systems.
- ContinuousImprovement & Innovation Stay updated with advancements in AI/ML,GenAI, and analytics ecosystems, and identify opportunities to improveexisting solutions and processes.
RequiredQualifications and Skills
- Experience Minimum 1–2years of hands-on experience in Data Science, Machine Learning, or AIsolution development with demonstrated project delivery experience.
- Education Bachelor’sor Master’s degree in Computer Science, Data Science, Engineering,Mathematics, Statistics, or related quantitative fields.
- ProgrammingLanguages Deep proficiency in Python and SQL is essential.
- ML/ AI expertise Hands-onexperience with machine learning libraries and frameworks such asScikit-learn, XGBoost, TensorFlow, PyTorch, or similar tools.
- Generative AI Exposure Experienceworking with LLMs, prompt engineering, vector databases, or GenAIframeworks is preferred
- Data Visualization Experiencewith dashboarding and visualization tools such as Power BI, Tableau, orsimilar platforms.
- Development Tools Familiaritywith VS Code, Git, notebooks, APIs, and collaborative developmentworkflows.
- MLOps & Deployment Basicunderstanding of MLOps concepts, CI/CD pipelines, model monitoring, andcloud-based AI deployments. Exposure to cloud platforms such as AWS,Azure, or GCP will be an advantage
- Preferred Experiencein production deployment of ML/AI solutions, experience integrating AIsolutions with APIs and enterprise systems, understanding of businessproblem solving using analytics and AI