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

Main Purpose:

Provide enterprise-wide strategic leadership in Clean Energy analytics by defining how advanced data science, AI, and decision intelligence drive long-term business transformation and sustainability outcomes.
Act as the principal authority on data science strategy, ensuring alignment with corporate goals, regulatory requirements, and clean energy transition objectives.
Lead and mentor multiple data science teams or domain leads, ensuring consistent delivery of high-impact, scalable analytics solutions across business units.
Partner with CXOs, executive leadership, and functional heads to shape analytics-led decisions, risk posture, and capital optimization strategies.
Architect, govern, and oversee the end-to-end lifecycle of advanced analytics, ML, and AI solutions, leveraging large-scale structured and unstructured data from subsurface, drilling, operational, and monitoring systems.

Job Accountabilities:

Define and monitor enterprise-level KPIs and value realization frameworks to measure business impact of analytics initiatives across safety, environment, production, and cost.
Establish advanced risk intelligence frameworks for operational, safety, environmental, and regulatory risk quantification using AI/ML.
Drive organization-wide data science governance, standards, and best practices, including model lifecycle management, ethics, explain ability, and compliance.
Own the multi-year data science and AI roadmap, aligning technology investments with business strategy in collaboration with Digital, IT, and Cybersecurity leadership.
Lead enterprise-scale AI initiatives such as predictive maintenance platforms, real-time anomaly detection systems, optimization engines, and forecasting solutions.
Guide the formulation of next-generation algorithms and AI products supporting clean energy transition, decarbonization, and digital innovation.
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:

Expert-level proficiency in SQL, Python, and enterprise-scale analytics development.
Deep mastery of advanced statistics, machine learning, AI, optimization, and experimental design, with the ability to guide methodological choices.
Proven expertise in big data and distributed computing architectures (Hadoop ecosystem, cloud-native analytics platforms).
Hands-on experience with statistical and modeling tools such as SAS, R, MATLAB, Statistical and advanced visualization platforms.
Advanced knowledge of time-series modeling, anomaly detection, and industrial sensor analytics in clean energy or large-scale operational environments. Strong understanding of data management, databases (SQL, PL/SQL), and data pipelines.
Exceptional executive communication, storytelling, and influence skills.

Experience Required:

Minimum 15 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.
Experience operating in highly complex, regulated, and asset-intensive environments.

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

Sr Lead Data Scientist