Description

The ideal candidate should possess strong expertise in statistical modeling, machine learning, AI, and emerging Agentic AI frameworks, along with experience in solving real-world automotive or manufacturing problems such as predictive maintenance, quality analytics, supply chain optimization, or connected vehicle use cases.

Responsibilities

- 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.

Qualifications

- 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

- Solid 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

📌 DTICI__Data_Scientist_Data_operations_R&D (Bengaluru)
🏢 Nameless
📍 Bengaluru