Interested candidates, kindly mail to enpcareers.hr@ril.com

Main Purpose:

Lead innovation in Clean Energy by defining how data science and analytics create measurable business value across operations and decision-making.
Oversee the data science team, ensuring alignment with business strategy and delivery of high-impact analytics use cases.
Partner with business leaders and functional heads to identify key risks, optimization opportunities, and data-driven interventions.
Design, develop, and deploy advanced analytics, machine learning, and predictive models using structured and unstructured data from subsurface, drilling, operational, and monitoring systems.
Lead the development and utilization of big data platforms to support clean energy analytics at scale.

Job Accountabilities:

Track operational performance against analytical models and monitor KPIs related to production efficiency, safety, environment, and cost.
Identify, monitor, and quantify operational, safety, and environmental risks using advanced analytics.
Drive adoption and evangelization of data science culture across business units through education, communication, and demonstrable use cases.
Define and manage the data science roadmap, capabilities, and infrastructure in collaboration with digital and IT teams.
Manage external analytics partners, vendors, and research collaborators.
Build and develop data science talent through role definition, recruitment, mentoring, and capability development.
Define scope, design, and implementation of ML/AI models to support initiatives such as predictive maintenance, anomaly detection, optimization, and forecasting.
Lead formulation and optimization of algorithms supporting clean energy products, services, and stakeholder outcomes.
Collaborate with digital leaders to ensure secure, reliable, scalable, and cost-effective analytics infrastructure and operations.
Ensure effective communication with internal teams, leadership, and stakeholders at all levels.

Skills Required:

High proficiency in programming and scripting languages such as SQL, Python or similar.
Strong expertise in probability, statistics, machine learning, experimental design, and optimization techniques.
Experience working with big data platforms and distributed systems (Hadoop ecosystem).
Hands-on experience with statistical and modeling tools such as SAS, R, MATLAB, Statistical and advanced visualization platforms.
Expertise in time-series analysis, anomaly detection, and sensor/operational data analytics relevant to clean energy operations.
Strong understanding of data management, databases (SQL, PL/SQL), and data pipelines.
Excellent documentation, communication, and presentation skills.

Experience Required:

Minimum 9 years of experience in data science, analytics, or advanced modeling roles, preferably at Senior / Leadership level.
Proven track record of leading high-performing data science teams delivering measurable business impact.
Demonstrated experience in advanced quantitative analysis and statistical modeling applied to complex operational environments.
Experience leading cross-functional teams in mid-to-large organizations.

Preferred Educational Qualification:

Masters / MS in Statistics, Engineering, Computer Science, or equivalent from a reputed Tier-I institute (desirable).
Bachelors / BS in Statistics, Engineering, or equivalent from a reputed university/college.

Interested candidates, kindly mail to enpcareers.hr@ril.com

Lead Data Scientist