ReNew Power—Data Scientist

Job description

Description: Working @ Renew Working here means you’ll be part of something genuinely special . Funded by marquee investors and guided by a unique set of values, ReNew is the leading renewable energy IPP in India in terms of total energy generation capacity. We take pride in providing opportunities to our employees to create, explore, express, take risks and grow. As a ReNewer, you’ll always be doing things that would be beneficial to millions. About Company Founded in 2011, ReNew, is one of the largest renewable energy companies globally, with a leadership position in India. Listed on Nasdaq under the ticker RNW, ReNew develops, builds, owns, and operates utility-scale wind energy projects, utility-scale solar energy projects, utility-scale firm power projects, and distributed solar energy projects. In addition to being a major independent power producer in India, ReNew is evolving to become an end-to-end decarbonization partner providing solutions in a just and inclusive manner in the areas of clean energy, green hydrogen, value-added energy offerings through digitalisation, storage, and carbon markets that increasingly are integral to addressing climate change. With a total capacity of more than 13.4 GW (including projects in pipeline), ReNew’s solar and wind energy projects are spread across 150+ sites, with a presence spanning 18 states in India, contributing to 1.9 % of India’s power capacity. Consequently, this has helped to avoid 0.5% of India’s total carbon emissions and 1.1% India’s total power sector emissions. In the over 10 years of its operation, ReNew has generated almost 1.3 lakh jobs, directly and indirectly. ReNew has achieved market leadership in the Indian renewable energy industry against the backdrop of the Government of India’s policies to promote growth of this sector. ReNew’s current group of stockholders contains several marquee investors including CPP Investments, Abu Dhabi Investment Authority, Goldman Sachs, GEF SACEF and JERA. Its mission is to play a pivotal role in meeting India’s growing energy needs in an efficient, sustainable, and socially responsible manner. ReNew stands committed to providing clean, safe, affordable, and sustainable energy for all and has been at the forefront of leading climate action in India. Job Description As a Data Scientist in ReD, you will be responsible for providing simple and intuitive solutions to the most complex problems in renewables industry. This will involve building machine learning and deep learning models which are coupled with contextual business knowledge. You will work with a world-class team of site managers, subject experts, data engineers and data scientists to build the next generation data-driven renewable company. Further responsibilities will include: - Implement data science solutions which may involve machine learning or data science techniques to increase and optimize outputs - Acquire extensive knowledge of renewables industry practices and implement tailor made techniques to solve problems relevant to the same - Assess the effectiveness and accuracy of data sources and data gathering techniques - Work closely with business and site teams to identify opportunities for leveraging data to drive business solutions - Create data trails to monitor pre-define KRAs and work relentlessly to improve them Our ideal candidate: - Good programming and logical skills - Working knowledge of R or Python programming language. Exposure to distributed and cloud computing is a plus - Knowledge of statistical approaches, incl. advanced machine learning techniques (e.g. Linear Regression, Logistic regression, Generalized Linear Model, Sampling Techniques, Time Series Analysis, Decision trees, Clustering, Principal Component Analysis, Factor Analysis, CART, Random Forest, Support Vector Machine, Gradient Boosting, XGBoost, Neural Networks, multivariate analysis, stochastic models, and sampling methods) and/or optimization - Excellent verbal and written communication skills - Ability to learn and implement new technologies quickly - Ability to uncover data trends to gain insights about expected behaviour and perform actions accordingly (prescriptive analytics) - Strong critical thinking and problem-solving skills with an analytical mind-set and go-getter attitude Programming skills: - Basic knowledge of at least 1 programming language - Python or R - Algorithms – Theoretical knowledge of at least 3-4 algorithms - Hands on implementation – Developed at least 1-2 models - Functional/ Domain expertise - - Worked for at least 2+ years as part of an analytics team responsible for model building and deployment Communication skills: - Basic level of articulation of theoretical concepts - Ability to communicate with cross functional roles is a plus Teamwork: - Displays ability to work both as an individual and as a self-motivated team player - Has worked in large teams with an agile setup in the past ReNew Values PIONEER Take bold calls and innovate; Deliver sustainable future value; Encourage creative and Inspirational ideas; Respond to change with agility. RESPONSIBLE Care for the planet; Deliver high-quality solutions to customers; Meet our commitments and uphold stakeholders' trust; Maintain the highest standards of ethics and integrity. EXCELLENCE Build and execute best in class & within time; Take charge and dive deep; Driven by results and impact; Experiment and embrace continuous improvement. PARTNER Collaborate across businesses, geographies and levels; Connected by trust and mutual respect; Engage as a well-networked community; Drive the clean energy transition together. At ReNew, we believe that each individual is unique, and we respect and value these differences. We hire people from all regions, geographies, languages, backgrounds, cultures, gender and age groups fostering a truly inclusive environment at work. We are committed to accelerating progress, generating equitable outcomes, and ensuring our culture is supportive for everyone. We demonstrate equality and integrity in our growth as a responsible company for all.