DTICI_T8_Data_Scientist_Data_operations_R&D

• Develop, validate, and deploy machine learning and AI models to solve business challenges.
• Apply statistical techniques (hypothesis testing, regression, Bayesian methods) to derive insights from complex datasets.
• Design and implement end-to-end data science pipelines, including data ingestion, feature engineering, model training, evaluation, and deployment.
• Build and operationalize Agentic AI systems (autonomous agents, multi-agent workflows, LLM-based reasoning systems).
• Work on time-series forecasting, anomaly detection, and predictive analytics for manufacturing/automotive use cases.
• Collaborate with cross-functional teams including data engineering, product, domain experts, and business stakeholders.
• Interface with IoT, telematics, MES, ERP, and connected vehicle platforms for data-driven insights.
• Ensure scalability and performance by deploying models using cloud-based solutions (Azure/AWS/GCP).
• Communicate findings effectively through visualizations, dashboards, and presentations.
• Stay current with advancements in AI/ML, including GenAI and Agentic AI ecosystems.

• Strong foundation in Statistics & Probability
  • Hypothesis testing, regression models, A/B testing, Bayesian methods
• Expertise in Machine Learning
  • Supervised & unsupervised learning, model tuning, ensemble techniques
• Hands-on experience with AI / Deep Learning
  • NLP, computer vision, deep neural networks (preferred)
• Experience with Agentic AI / Generative AI
  • LLMs (GPT, Llama, etc.), prompt engineering, RAG, autonomous agents
• Proficiency in Python (mandatory)
  • Libraries: Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch
• Experience with Data Platforms
  • Snowflake / Databricks / Spark / SQL
• Experience in Model Deployment
  • APIs, Docker, MLflow, CI/CD pipelines
• Familiarity with Cloud Platforms
  • Azure (preferred), AWS, or GCP
• Experience in Automotive or Manufacturing domain, including:
  • Predictive maintenance
  • Quality analytics & defect detection
  • Supply chain optimization
  • Production planning & optimization
  • Connected vehicle / telematics analytics
  • IoT data processing
• Strong analytical and problem-solving mindset
• Ability to explain complex models to non-technical stakeholders
• Excellent communication and storytelling skills
• Team-driven mindset with stakeholder management experience

Preferred Qualifications :- 

• Experience working with streaming data (Kafka, Spark Streaming)
• Knowledge of Digital Twins / Industry 4.0 concepts
• Exposure to MLOps frameworks
• Experience with graph-based AI or multi-agent systems
• Understanding of data governance and model explainability