Job ID 21486
Career Level Mid-Level
Experience 2 Years
Qualifications Bachelor’s Degree (BSC)
ENGIE is a leading global energy company that builds its businesses around a model based on responsible growth to take on energy transition challenges. We provide individuals, cities and businesses innovative solutions based on our expertise in 4 key sectors: independent power production, natural gas, renewable energy and energy efficiency services to a low-carbon economy: access to sustainable energy, climate-change mitigation and adaptation and the rational use of resources.Job Purpose/Mission
We are looking for a talented, full-stack data scientist to join the digital team to help deliver affordable solar power to emerging markets. This position offers a great opportunity to work alongside an elite team of data scientists and business professionals and directly contribute to the success of a mission driven company with social and environmental impact. Candidates will get the opportunity to work in a diverse technology stack at scale. .
Deploy and maintain data pipelines and machine learning models to predict repayment, solar system device performance, credit scoring and other metrics which are key to the business.
Contribute to design and maintenance of an analytics database to empower data-driven decisions by analysts and strategists across the organization.
Design randomized, controlled experiments to understand levers available to improve customer repayment.
Perform analyses, with statistical components as appropriate, for department leaders to evaluate the impact of pilots and other interventions.
Leverage external data sources to help EEA grow its business and maximize social impact on customers in emerging markets.
Train data users across nine markets and the global team on data tools / skills to grow data capacity and culture at EEA.
Knowledge and skills
3+ years of relevant experience
Strong Python, especially in a data analytics/science capacity (ex. pandas, numpy, sklearn, matplotlib)
Facility with MySQL/Redshift
Experience with experimental design, statistical analysis, and interpretation of qualitative and quantitative data.
Good knowledge of statistical tests and analysis
Ability to communicate model outputs and analyses to stakeholders at various levels of technical expertise
Experience deploying predictive models at scale
Keen eye for detail and thoughtful investigation of data before relying upon it
Demonstrated expertise in strategic analysis to impact decisions
Thrives on teamwork
Bonus: Experience with financial data or credit scoring
MA or PhD in a relevant discipline (Data Science, Software Engineering, Statistics, or another relevant STEM field)
French, Swahili or Portuguese is a plus
Python or R, jupyter notebooks
Airflow (or other workflow management systems, such as Luigi)
Knowledge of Amazon Web Services (AWS) and its services, such as, but not limited to, Cloudwatch, RDS, Redshift, Lambda, EMR, S3, SQS, EC2
AWS environment: Cloudwatch, RDS, Redshift, Lambda, EMR, SQS, EC2
Statistical analysis and predictive modeling in python (scipy, stats, sklearn, etc)