Job Title:   Data Scientist

Organisation: ENGIE Energy Access (EEA)

Duty Station:   Kampala, Uganda

Reports To:    Head of Data

About US:

ENGIE Energy Access (EEA) is one of the leading Pay-As-You-Go (PAYGo) and mini-grids solutions provider in Africa, with a mission to deliver affordable, reliable and sustainable energy solutions and life-changing services with exceptional customer experience. The company is a result of the integration of Fenix International, ENGIE Mobisol and ENGIE PowerCorner; and develops innovative, off-grid solar solutions for homes, public services and businesses, enabling customers and distribution partners access to clean, affordable energy. The PAYGo solar home systems are financed through affordable installments from $0.19 per day and the mini-grids foster economic development by enabling electrical productive use and triggering business opportunities for entrepreneurs in rural communities. With over 1,700 employees, operations in 9 countries across Africa (Benin, Cote d’Ivoire, Kenya, Mozambique, Nigeria, Rwanda, Tanzania, Uganda and Zambia), over 1.2 million customers and more than 6 million lives impacted so far, ENGIE Energy Access aims to remain the leading clean energy company, serving millions of customers across Africa by 2025.

Job Summary:   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 Duties and 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 integrity 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.

• Bachelors or master’s in computer science, machine learning, or related field

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
• Language(s):
• English
• French is a plus.

 Technology: 

• Python, R, Java, SQL, NoSQL, Amazon Redshift, Kafka, Apache Beam, Apache Airflow, Apache Spark