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  • Posted: Jul 19, 2021
    Deadline: Not specified
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    Pezesha, has created a holistic financial marketplace for MSMEs. By offering lending, financial education, and debt counselling to borrowers, plus a proprietary credit scoring system to vet MSMEs without a credit history, derisking lending to SMEs. Lower Risks bring commercial banks and capital providers onto Pezesha platform. As a collaborative structure, Pezesha is helping to tackle the $19 Billion financing gap for SMEs. Pezesha is led by a highly experienced and passionate local team with more than 10 years local and international experience in fin-tech, management of growth and technology companies, and unparalleled local market knowledge and reach.
    Read more about this company

     

    Business Data Analyst

    We are looking for a rockstar data nerd with previous experience working with large data sets, and is familiar with techniques and approaches to data. They will also help interpret data into models and decisions that guide the company to assess and predict credit risk to SMEs we fund.

    Primary responsibilities;

    • Data analysis using statistical techniques
    • Data cleaning and data mining
    • Conducting full lifecycle analysis to include requirements analysis, data cleaning and design in relation to data needs and come up with workflows while communicating effectively with stakeholders and working closely with the data and technical team
    • Internal data analysis & reporting by developing intelligent, descriptive, predictive and spatial models
    • Provide strategic data driven decisions and recommendations to the business initiatives and other external stakeholders to ensure robust products developments and scale
    • Lead problem solving experiments and coordination efforts between various business units while measuring results effectively and efficiently for each experiment
    • Business intelligence to maximize proficiency and productivity with our products and services. 

    Must haves;

    • Minimum Education: Undergraduate degree in Mathematics, Statistics, Economics or similar
    • Experience analysing data: evidence that you can communicate the key messages from large data sets
    • Excellent with SQL database operations
    • Technical skills regarding data models, database design development, data mining and segmentation techniques
    • Experience cleaning data: ensuring the data collected is in a usable format and diagnose when it’s not: a good level of Quality Assurance.
    • Excellent communication and collaboration skills: you will work closely with the data and tech teams to define partner requirements/needs, defining the right data solutions 
    • You can think critically about a business, understand its key drivers and be able to dynamically model different scenarios
    • Attention to detail: Meticulous, Fastidious, thorough
    • Strong analytical skills

    Experience required:

    • Experience with analytics and business intelligence tools: e.g. Power BI, Tableau, MS Power BI, SPLUNK etc
    • 2+ years of relevant experience in data fields
    • Knowledge of statistics and experience using statistical packages for analyzing datasets (Excel, SPSS, SAS etc)
    • Familiar with ETL process (Extract, Transform and Load)
    • Experience with experimental design, statistical analysis, and interpretation of qualitative and quantitative data.
    • Good knowledge of statistical tests and analysis
    • Ability to balance priorities, clarify stakeholder requirements, pay keen attention to detail, and generally keep deliverables on schedule
    •  Ability to communicate technical details clearly and concisely to management & external stakeholders
    • A curious mind and a passion for problem-solving, data, and analytics
    • Comfort in a fast-paced, growth-stage start-up environment

    Good to have;

    • Experience in developing credit scoring models
    • Python skills especially in a data analytics capacity

    Method of Application

    Interested and qualified? Go to Pezesha on www.linkedin.com to apply

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