Senior Data Scientist ML, Python

Job description

Job Title: Data Scientist (AI/ML) – Data Engineering & MLOps Role Summary We are seeking a hands-on Data Scientist who can operate across data engineering and machine learning to deliver production-ready analytics/AI solutions. This role includes building data pipelines and curated datasets, developing and evaluating ML models, and supporting model operationalization with MLOps practices across the ML lifecycle (from data discovery through deployment and monitoring). Key Responsibilities Partner with business and technical stakeholders to translate problems into data-driven and ML solutions , communicating insights and model outcomes clearly Perform exploratory data analysis , feature engineering, and build predictive/advanced analytics models using Python-based DS libraries. Design, build, and maintain data pipelines and datasets to support analytics and model training (batch/near-real-time as needed). Apply MLOps discipline across the ML lifecycle: data validation, packaging, deployment support, and performance monitoring concepts. Collaborate in Agile delivery (sprint goals, user stories, iteration based on feedback). Required Skills & Experience Strong hands-on Python for data analysis and ML model development. Experience with data engineering fundamentals : data integration, data processing, and pipeline/orchestration concepts. Solid grounding in ML lifecycle / MLOps concepts (validation, versioning, deployment, monitoring). Ability to assess data sources for quality, relevance, and usability; translate business rules into analytics logic. Strong communication skills—able to bridge business stakeholders and technical teams. Preferred / Nice to Have Cloud exposure (AWS/Azure) and understanding of operationalizing ML solutions (CI/CD, monitoring patterns). Experience with modern AI/GenAI patterns (e.g., RAG/LLMs/knowledge graphs) if project requires it. Experience building reliable production-grade AI pipelines and data quality monitoring. Key Responsibilities 1. Design And Implement Advanced Machine Learning Algorithms Using Tensorflow And Pytorch To Extract Insights From Large Datasets, Delivering Customized Analytical Reports Tailored To The Needs Of Colleagues, Clients, And Stakeholders. 2. Leverage Python And Sql To Develop And Optimize Data Models That Address Specific Organizational Challenges, Ensuring Effective Integration And Management Of Data. 3. Analyze And Mine Large Datasets To Identify Trends And Patterns, Utilizing Advanced Analytics Techniques To Interpret Findings And Provide Actionable Recommendations Based On Experimental Results. 4. Collaborate With Cross-Functional Teams To Identify Opportunities For Utilizing Data Insights To Formulate Strategic Business Solutions That Enhance Operational Efficiency And Product Offerings. 5. Create Comprehensive Visualizations And Reports Using Data Visualization Tools To Communicate Complex Analysis And Results Clearly, Enabling Informed Decision-Making For Customers And Stakeholders. Skill Requirements 1. - Strong Knowledge Of Machine Learning Principles And Algorithms Using Tensorflow And Pytorch. 2. - Proficient In Programming Languages Such As Python For Data Analysis And Model Development. 3. - Solid Understanding Of Sql For Data Manipulation And Querying Large Databases. 4. - In-Depth Experience With Data Analytics Techniques And Tools For Interpreting Complex Datasets. 5. - Excellent Collaboration And Communication Skills To Work With Diverse Teams And Stakeholders. Other Requirements 1. Optional But Valuable Certifications: Certified Data Scientist (Cds), Tensorflow Developer Certificate, Or Professional Data Engineer Certification. Apply now Information at a Glance Why HCLTech? At HCLTech, you'll supercharge your potential. You'll find your career. And you'll find your spark. All at a place that knows that helping its customers stay on top starts by putting its people first. HCLTech is a global technology company, home to more than 223,000 people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending June 2026 totaled $14.8 billion. Disclaimer Privacy Statement Terms of use Sitemap Raise a Grievance We use cookies on our site. Please read more about cookies policy here. Opens in a new tab. Opens in a new tab. Opens in a new tab. Opens in a new tab. Opens in a new tab. Opens in a new tab. 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