Data Scientist, Data Operations, R&D

Jobtailor; Bengaluru; On-site; INR 1,800,000 - 3,400,000; Full time

Job summary

Jobtailor in Bengaluru is seeking a skilled Data Scientist to design and deploy enterprise AI/ML solutions. The role focuses on building end-to-end data pipelines, validating models, and operationalizing AI systems in automotive or manufacturing contexts.

You will collaborate with cross-functional teams, handle streaming data, and communicate insights through dashboards and presentations. A strong background in statistics and ML is essential, with hands-on Python expertise and cloud experience.

Qualifications

• 4–5 years of data science experience in enterprise settings.
• Strong foundation in Statistics & Probability.
• Expertise in Machine Learning and AI/Deep Learning.
• Experience with Agentic AI / Generative AI.
• Proficiency in Python and data platforms for end-to-end pipelines.
• Experience deploying models and leveraging cloud platforms.
• Familiarity with automotive or manufacturing domains is a plus.
• Ability to explain complex models to non-technical stakeholders.
• Excellent communication and storytelling abilities.
• Team-oriented with stakeholder management experience.
• Experience with streaming data and Industry 4.0 concepts is preferred.
• Exposure to MLOps frameworks and graph-based AI is preferred.
• Understanding of data governance and model explainability is preferred.

Responsibilities

• Design, build, and deploy advanced analytics and AI/ML solutions in enterprise environment.
• Develop, validate, and deploy ML and AI models to solve business challenges.
• Apply statistical techniques to derive insights from complex datasets.
• Design and implement end-to-end data science pipelines.
• Build and operationalize Agentic AI systems.
• Work on time-series forecasting, anomaly detection, and predictive analytics.
• Collaborate with 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.
• Communicate findings effectively through visualizations, dashboards, and presentations.
• Stay current with advancements in AI/ML.

Skills

Statistical analysis

ML development

Python programming

Communication skills

Stakeholder management

Problem solving

Streaming data experience

Industry 4.0 knowledge

MLOps exposure

Multi-agent systems

Data governance understanding

Tools

Python

Cloud platforms

Data Platforms

Model Deployment

Job description

Responsibilities

• Design, build, and deploy advanced analytics and AI/ML solutions in enterprise environment
• Develop, validate, and deploy machine learning and AI models to solve business challenges.
• Apply statistical techniques to derive insights from complex datasets.
• Design and implement end-to-end data science pipelines
• Build and operationalize Agentic AI systems
• Work on time-series forecasting, anomaly detection, and predictive analytics
• 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
• Communicate findings effectively through visualizations, dashboards, and presentations
• Stay current with advancements in AI/ML

Requirements

• 4–5 years of experience in data science
• Strong foundation in Statistics & Probability
• Expertise in Machine Learning
• Hands‑on experience with AI / Deep Learning
• Experience with Agentic AI / Generative AI
• Proficiency in Python
• Experience with Data Platforms
• Experience in Model Deployment
• Familiarity with Cloud Platforms
• Experience in Automotive or Manufacturing domain
• 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
• Experience working with streaming data (preferred)
• Knowledge of Digital Twins / Industry 4.0 concepts (preferred)
• Exposure to MLOps frameworks (preferred)
• Experience with graph-based AI or multi‑agent systems (preferred)
• Understanding of data governance and model explainability (preferred)