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    Data Scientist – Technical Lead At ECOM Agroindustrial Corp. Ltd


    February 15th, 2022 at 05:54 am

    ECOM Agroindustrial Corp. Ltd is a global commodity trading and processing company specializing in coffee, cotton and cocoa in major producing and consuming countries, with other ancillary agricultural operations and products.

    ECOM is one of the world’s top three merchants in coffee, one of the largest coffee millers in the world, and among the top five merchants in both cotton and cocoa.

    Based in GHANA – As an origin‐integrated business operating in over 40 major producing countries worldwide, ECOM focuses primarily on coffee, cotton, and cocoa. In West Africa, ECOM is one of the leading cocoa companies operating between farm gate and chocolate maker clients. We also trade in other crops, such as cashew and sesame.

    We provide advisory services, training and support to farmers on productivity, quality, certification, and crop diversification, environmental and broader social issues. We also run a fleet of over 150 modern trucks that serves our logistics and transport needs. We provide farmers with relevant products including a range of agro‐inputs and micro‐financing options. The company impacts the livelihoods of over 250,000 smallholder farmers.

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    In Ghana, Ecom is made up of six (6) fast growing entities.

    POSITION: Data Scientist – Technical Lead

    About the Role

    Based in GHANA – ECOM Agrotrade, a leading global commodity merchant and sustainable supply chain management company, is seeking a Data Science Technical Lead to be part of Data Insights team to use statistical models and machine learning (ML) techniques to design and develop relevant artificial intelligence (AI) models.

    The Data Science Technical Lead will be working with ECOM’s Data Insights and will have a passion for data and analytics with the willingness to dig deep into details as well as the ability to assess the big picture. In-depth understanding of modeling techniques and the ability to perform in a team is critical to success in this role.

    Having a skilled and dedicated resource for developing statistical analysis using different programming or systems and helping to build and strengthen the data analytics processes that will bridge existing gaps is a key part of Data Insights’ strengthening efforts.

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    The Data Science Technical Lead should have strong foundational knowledge of data analysis and ML, knowledgeable in the ML pipeline, and will make sure that the AI/ML projects within ECOM are successfully implemented according to the appropriate methods and quality standards to meet business requirements.

    The Data Science Technical Lead will work collaboratively with an implementation team to execute AI/ML projects. He/She will lead efforts to mine through data to identify opportunities to improve efficiencies or optimize business outcomes.

    The position is based at Ecom’s Ghana Head Office in Kumasi.

    Your responsibilities will include:

    • Lead efforts to identify opportunities where AI/ML could be effectively applied to solve analytically challenging problems in ECOM, articulate AI/ML project requirements, plan, and prioritize such projects.
    • Lead efforts to test state of the art ideas for their applicability and galvanize business leaders and stakeholders to put the best ones into use.
    • Lead efforts to build and manage the AI/ML pipelines iteratively that provide actionable insights.
    • Research and develop analyses, optimization, forecasting methods across ECOM’s business areas and operations.
    • Provide solutions to business problems using data analysis, data mining, optimization tools, statistical modeling, and machine learning techniques.
    • Actively seek opportunities to innovate by using non-traditional data and new analytics methodologies.
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    Who we are looking for:

    • Minimum qualification: Master’s degree or equivalent experience in quantative field (Statistics, Mathematics, Computer Science, Engineering, etc.)
    • At least 4 years’ of experience in data analysis, machine learning, and AI.
    • Experience of statistical data analysis (linear models, multivariate analysis)
    • Proven advanced experience with statistical software (Python, R, pandas, MATLAB) and database languages.
    • Experience in articulating business questions and using mathematical techniques to formulise answers using available data.

    HOW TO APPLY

    CLICK HERE TO APPLY ONLINE

    CLOSING DATE: MARCH 4, 2022

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