AI & Data Analytics Specialist

Role & Responsibilities

• Design, develop and support data analytics, business intelligence, and AI-driven solutions for business functions across the organization.
  
• Collaborate with business and IT stakeholders to understand requirements, define analytical use cases, and deliver measurable outcomes.
  
• Extract, clean, transform, and analyze data from ERP systems, databases, spreadsheets, APIs, and other enterprise data sources.
  
• Develop dashboards, reports, visualizations, and self-service analytics solutions using Power BI and related tools.
  
• Build and deploy machine learning and AI models for forecasting, classification, anomaly detection, optimization, and decision support.
  
• Develop Proof of Concepts (PoCs) and convert successful solutions into scalable and maintainable applications.
  
• Integrate analytics and AI solutions with enterprise applications through APIs and automated data pipelines.
  
• Monitor data pipelines, dashboards, and deployed models to ensure data quality, reliability, and performance.
  
• Create technical documentation, user guides, and support deployment, training, and post-implementation activities.
  

Preferred Candidate Profile

• B.Tech./B.E. in Computer Science, Information Technology, Data Science, Statistics, Analytics, or a related discipline. MCA/M.Sc. candidates are also welcome.
  
• 4-7 years of hands-on experience in Data Analytics, Business Intelligence, Data Science, Machine Learning, or AI solutions.
  
• Strong programming skills in Python and SQL with experience in data preparation, analysis, automation, and reporting.
  
• Hands-on expertise in Pandas, NumPy, Scikit-Learn, and data visualization tools such as Power BI, Matplotlib, Seaborn, or Plotly.
  
• Good understanding of ETL/ELT, Data Warehousing, Data Modeling, and Data Engineering concepts.
  
• Experience in Machine Learning, Predictive Analytics, Statistical Modeling, and Decision Support Systems.
  
• Exposure to Generative AI, Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), and AI integrations will be an added advantage.
  
• Experience working with REST APIs, analytics platforms, and enterprise applications.
  
• Exposure to manufacturing, supply chain, finance, sales, or ERP analytics environments will be preferred.
  
• Strong analytical, problem-solving, communication, and stakeholder management skills.