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
- This position will be part of the Global Data team. This is an incredible opportunity to join a high-performing team that is passionate about pioneering expanded financial services to off-grid customers at the base of the pyramid.
- Key responsibilities will include building and maintaining data models to support sales and customer finance operations.
- You would also be involved in data mining activities as well as engage with internal business stakeholders in realtime to our field team mobile application to allow data-informed decisions to be made in the field, as well as working with members of the data team to ensure high code quality and database design.?
- Your work will make a meaningful impact by enabling Engie to continuously innovate on how we support our customers in their repayment journey.?
Key Competencies
Responsibilities
Data Mining (20%):
- Design and implement robust data mining models to support analytics and reporting requirements.
- Carry out pre – processing, cleansing, and validating the integrioty of data to be used for analysis
- Enhance data collection procedures to include all relevant information for developing analytic systems.
Statistical modelling (70%)
- Use statistical and machine learning techniques to develop solutions to support business operations from sales to credit collection.
Stakeholder management (10%)
- Communicate results with stakeholders within the business operations teams.
Experience:
- 5+ years of industry experience?working on data scientist with a focus on data modelling, stakeholder management and data mining.,
- Proficiency using machine learning frameworks like keras, pytorch, Tensorflow, sckit-learn, statistical tools (statistical tests, distribution, regression, maximum likelihood estimators, strong math skills (multivariate calculus, linear algebra), machine learning methods (k-Nearest Neighbours, Naive Bayes, SVm, Decision forests), Data visualization tools (matplotlib, d3.js, Tableau).
- Experience working with structured and unstructured data using Python, R, Scala, Java, SQL in addition to one or more of Spark/Hadoop/Hive/HDFS?, Apache Airflow, RabbitMQ/Kafka, Spark, Kubernates, and dbt.
- Working knowledge of databases, data systems, and analytics solutions, including proficiency in SQL, NoSQL, Java, Spark and Amazon Redshift for reporting and dashboard building.
- Experience with implementing unit and integration testing.
- Ability to gather requirements and communicate with stakeholders across data, software, and platform teams.
- Deep understanding of data structures, data modelling and architecture.
- Experience managing a team of mid-level data scientists.
- Sense of adventure and willingness to dive in, think big, and execute with a team
Qualifications:
- Bachelors or master’s in computer science, machine learning, or related field
Language(s):
- English
- French is a plus.
Technology:
- Python, R, Java, SQL, NoSQL, Amazon Redshift, Kafka, Apache Beam, Apache Airflow, Apache Spark
Method of Application
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