Lead Data Scientist

SLB Pune, Maharashtra, India (Hybrid)

About us

We are a global technology company, driving energy innovation for a balanced planet.​ Together, we create amazing technology that unlocks access to energy for the benefit of all.​Our inclusive culture is the key to our success. We collaborate with our internal community of colleagues, alumni, and our valued external partners to support each other and achieve our goals. We aim to raise the bar high. We look for people who are committed to innovation and success and act with integrity to become and be a part of one of the most diverse group of experts in our industry, anywhere around the globe. Global in outlook, local in practice - and with a united, shared passion for discovering solutions, we hire talented, driven people and support them to succeed, personally and professionally.

About SLB Technical Services India (STS-I):

SLB is committed to moving farther and faster in facilitating the world's energy needs today and forging the road ahead for the energy transition. STSI’s determination to transformation is the start of a journey towards a culture of continuous performance improvement. Over the years STSI has also developed key expertise and support roles in higher scale work both in business vertical (within a PG) and horizontal (across PGs). To position itself as a critical support center for EMS capable of strong value addition while also being recognized as having their own excellence in key services, STSI has identified the need to attain a recognition as a Center of Excellence (CoE).

For more details you may visit our Company’s Official site: www.slb.com

Job Description:

The Lead Data Scientist will be responsible for driving the technical vision, execution, and delivery of Prognostics & Health Management (PHM) solutions for industrial equipment and digital products. This role combines technical leadership with hands-on data science responsibilities and requires a strong foundation in analytics, machine learning, time-series modelling, and industrial sensor data analysis.

The successful candidate will lead a team of approximately 10 Data Scientists and work closely with domain experts, reliability engineers, product owners, software teams, and business stakeholders to develop scalable predictive maintenance, diagnostics,



and prognostics solutions that improve equipment reliability, availability, and operational efficiency.

Key Responsibilities

- Lead, mentor, and grow a team of Data Scientists, fostering technical excellence, innovation, and continuous learning.
- Define and drive the technical roadmap for PHM (Prognostics & Health Management) and predictive analytics initiatives across multiple product lines.
- Serve as the technical authority for machine learning, advanced analytics, and time-series modelling activities.
- Remain hands-on in the development, validation, and deployment of machine learning and AI solutions.
- Develop diagnostic, anomaly detection, prognostic, and remaining helpful life (RUL) prediction models using large-scale industrial sensor data.
- Collaborate with engineering SMEs to understand equipment behaviour, failure modes, electronics systems, control systems, and operational workflows.
- Translate complex business and engineering challenges into scalable AI and data science solutions.
- Drive adoption of modern AI approaches including Generative AI, LLM-based solutions, knowledge assistants, and intelligent analytics workflows where appropriate.
- Establish best practices for data science development, code quality, model governance, experimentation, and MLOps.
- Work with cloud-native architectures and contribute to end-to-end deployment of analytics solutions on platforms such as Google Cloud Platform (GCP) and Microsoft Azure.
- Communicate technical findings and business impact effectively to senior leadership and stakeholders.
- Quickly develop domain expertise across new equipment types, business applications, and operational environments.

Skills Required
- Strong expertise in Data Science, Machine Learning, and Advanced Analytics.
- Deep understanding of time-series modeling, predictive maintenance, PHM, anomaly detection, and sensor data analytics.
- Proficient in Python, SQL,



and modern ML/AI frameworks.
- Experience with industrial/IoT data; Electronics, Instrumentation, or related engineering background is preferred.
- Exposure to Generative AI, LLMs, MLOps, and cloud platforms (GCP and/or Azure).
- Proven ability to lead and mentor Data Science teams while remaining hands-on.
- Strong problem-solving, stakeholder management, communication, and technical presentation skills.
- Quick learner with the ability to rapidly acquire business and domain knowledge and translate it into impactful analytics solutions.

AI & Technology Skills
- Advanced Python programming skills.
- Experience with:
- Generative AI and Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- AI Agents and Copilot technologies
- MLOps and model lifecycle management

- Experience with:

- SQL
- Git
- CI/CD practices
- Docker and containerization

Cloud & Data Platforms
- Hands-on experience with Google Cloud Platform (GCP) and/or Microsoft Azure.
- Experience with cloud-native analytics architectures.
- Knowledge of:
- Big Query
- Azure Data Services
- Data Lakes
- Distributed processing environments
- Model deployment and monitoring frameworks

Qualifications and Experience
- Bachelor's degree in Data Science, Computer Science, Electrical Engineering, Electronics Engineering, Mechanical Engineering, Physics, Mathematics, or a related technical discipline.
- Master's degree or higher in Data Science, Artificial Intelligence, Analytics, Statistics, Computer Science, or Engineering preferred.
- 7+ years of experience in Data Science, Machine Learning, Analytics, or Industrial AI.
- 2+ years of experience leading or mentoring Data Science teams.
- Demonstrated experience delivering production-grade machine learning solutions from concept to deployment.
- Experience in PHM, predictive maintenance, asset reliability, IoT analytics, industrial AI, or related domains is highly preferred.

This is an office-based position, with the expectation to come into the office four days a week.

SLB is an equal employment opportunity employer. Qualified applicants are considered without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, age, disability, or other characteristics protected by law.

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