Manager - Data Science

BURN

In 1990, Peter Scott was traveling through Zaire when he witnessed the deforestation caused by charcoal production for household cooking. At that moment, he committed his life to save forests in Sub-Saharan Africa through the design and manufacture of fuel-efficient cookstoves.

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Manager - Data Science

Institution:  BURN

Location: Nairobi

Job Type: Full Time

Job description

The role involves working in an environment with gigabytes of data from multiple sources and company data warehouses to extract insights that can be beneficial for the Organization. The responsibilities will therefore span across the entire data value chain from locating and assembling data, building datasets for analysis, implementing and interpreting mathematical and statistical procedures that often involve novel, challenging analyses of large datasets, and creating final presentations, reports, and graphics, while working closely with other managers and principal consultants to deliver to all stakeholder expectations including internal customers like commercial, new product development, expansion and externals like investors, funding partners, auditors.

Roles & Responsibilities

  • Data management: work with big data/large data sets, manage and manipulate them through data programming and scripting tools like Python, R, Ms Excel VBA et al.
  • BI reporting; Develop BI reports, dashboards, and data models with the help of BI tools and MS-365 products and present consequent reports to management.
  • Review and validate homegrown data as it’s collected and from various sources, create, discover, and implement new data analysis, visualization, and processing programs.
  • Work closely with all departments that generate and consume homegrown data including after sales, market research, commercial, carbon, expansion and new product development to validate data sources and deliver quality data output that is usable for strategic decision making.
  • Develop data management protocols, working alone or partnering with other programmers and other relevant internal stakeholders, aid in the design, development and implementation of new programs and application for managing big data.
  • Design and implement projects data-needs solutions; review project data needs and recommend designs, implement them and work to continually improve them.
  • Processing, cleaning, and verifying the integrity of data used for analysis and reporting.
  • Creating automated anomaly detection systems and constant tracking of its performance
  • Work closely with data systems suppliers to maintain expected standards of data integrity for all data related projects.
  • Cooperate with IT department to deploy software and hardware upgrades that make it possible to leverage big data.
  • Monitor critical analytics and metrics results and communicate the same effectively and in a timely manner to user departments and any other external stakeholders.
  • Develop policies and procedures/SOP’s for the collection and analysis of data.
  • Data warehouse system: Design and oversee the deployment of data to the data warehouse systems.
  • Machine learning: Spearhead designing, developing, and maintaining machine learning algorithms that would enhance and improve the data handling environment in the organization.

Skills & Qualifications:

  • At least 4 years’ experience in a BI or data science environment
  • Have at least a degree in Applied statistics/ Mathematics/ Actuarial science/ Data science/ Economics & Statistics/ Operations research
  • Experience in machine learning algorithms.
  • Proficiency with at least one programming language for data science e.g. R, Python, SAS, MS Excel etc.
  • Proficiency in database management and query languages e.g., SQL, MySQL as well as data warehouse set up & management.
  • Experience in team leadership, cross-department functioning and reporting/presentation to c-suite and senior management.

Degree qualifications

Bachelor’s Degree

Method of Application

Go to  https://burnstoves.com/careers/position?s=manager-data-science   

Closing: Thu, 30 Sep 2021

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