Data Scientist - Ecobank


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Ecobank IT Jobs in Ghana


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Job Purpose

Reporting to the Lead, Data Science, the Data Scientist will support work on our core business products and customer transactions by assisting in the development of machine learning models under guidance and using industry best practice.

The Data Scientist will apply developing programming skills to assist with building, deploying, implementing, and maintaining predictive models and rating algorithms. The individual in this role will gain familiarity with different ways of capturing data, including REST APIs, and support the building of pipelines for real-time consumption and analysis of internal and external data sources.

Job Context

Supporting hypothesis testing, machine learning and analytical designs for prediction, forecasting, and product and business development, with guidance from senior colleagues.


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Key Responsibilities

  • Apply developing skills in quantitative analysis, data mining, and the presentation of data to help see beyond the numbers and understand how our customers and users interact with both business products and systems.
  • Assist in designing and evaluating data experiments.
  • Support the monitoring of key product metrics.
  • Help build key data sets to empower operational and exploratory analysis.
  • Assist in evaluating and defining metrics for the data warehouse.
  • Contribute to understanding user behaviours and long-term trends.
  • Support product teams through the presentation of data-based recommendations.
  • Help communicate state of business, experiment results, etc. to product teams.
  • Gain exposure to the Big Data ecosystem (Hadoop, Hive, MapReduce) and, where required, MySQL and Oracle.
  • Assist in building and maintaining pipelines via querying tools and the ETL framework for the Data Warehouse.
  • Collaborate with the analytics team to help formulate innovative solutions and support the application of modelling techniques.
  • Support the identification of business opportunities through data mining.
  • Partner with other units of the team to fulfil ad-hoc data requests and respond to business enquiries in a timely manner.
  • Provide L1/L2 support alongside junior colleagues, managing and resolving the team’s tickets through the SysAid ticket management system.

Job Profile

Experience & Qualifications

  • B.A. / B.Sc. in Computer Science, Math, Physics, Engineering, Economics, Statistics or other technical field.
  • Some experience in SQL or other programming languages.
  • Basic development exposure to at least one scripting language (Python, PHP, Perl, etc.).
  • Ability to communicate the results of analyses in a clear and effective manner with product and leadership teams.
  • Foundational understanding of statistics (e.g., hypothesis testing, regression analysis).
  • Growing ability to manipulate data sets through statistical software (e.g., R, SAS, SPSS or Minitab) or other methods.
  • Passion for working with big data and an interest in customer and financial models.
  • Awareness of Data Warehouse design and strategy concepts.
  • Understands relational database and star schema concepts.
  • Understands data profiling and data quality/testing concepts.
  • Experience with Microsoft Excel / PowerPivot.
  • Financial industry experience is a plus.
  • Strong analytical skills, problem-solving, and attention to detail.
  • Foundational exposure to statistical modelling techniques.
  • Exposure to Big Data technologies.
  • The ability to understand unique business needs and translate them into technical requirements, with support.


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Skills, Capabilities & Direct Attributes

  • Demonstrated ability to handle multiple projects and deadlines.
  • Must be Customer Service oriented.
  • Must be a result-driven and action-oriented individual.
  • Must be a true Team player.
  • Must also be self-motivated and able to work independently and autonomously when asked.
  • Must possess strong analytical and problem-solving skills.
  • Must possess strong abilities and interest in analyzing and extracting useful, business-related information from large amounts of Customer and pricing data.

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