DTICI_T8_Data_Scientist_Data_operations_R&D
Data ScientistData
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Quick Summary
Requirements Summary
- Experience working with streaming data (Kafka, Spark Streaming) Knowledge of Digital Twins / Industry 4.
Technical Tools
Data ScientistData
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.
- 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
Requirements
~1 min read- 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
Location & Eligibility
Where is the job
Bangalore, India
Hybrid, some on-site time required
Who can apply
IN
About this job
- Who can apply
- India
- Posted
- 100 days ago
Listing Details
- Posted
- July 8, 2026
- First seen
- July 8, 2026
- Last seen
- August 30, 2026
Posting Health
- Days active
- 99
- Repost count
- 0
- Trust Level
- 23%
- Scored at
- October 16, 2026
Signal breakdown
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