Data Scientist at BCMCF Lesotho

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Overview:

KARABO EA BOPHELO at Baylor College of Medicine Children’s Foundation – Lesotho. The Baylor College of Medicine Children’s Foundation – Lesotho (BCMCFL), is the result of a public-private partnership between Baylor College of Medicine International Pediatric AIDS Initiative and the Government of Lesotho, and is a legal, non-profit/tax exempt organization registered in Lesotho. BCMCFL provides free pediatric and family-centred HIV and tuberculosis prevention, care, treatment, and support, serving thousands of children and families affected by HIV, TB, or other child health conditions. Karabo ea Bophelo (KB) is a five-year USAID-funded activity to prevent new HIV infections and reduce vulnerability among orphans and vulnerable children (OVC) and adolescent girls and young women (AGYW) in Lesotho.

BCMCFL is looking for highly qualified local candidates to fill in the following positions available under Karabo ea Bophelo Project on a full-time, Fixed-Term Contract basis.

Position

Data Scientist x 1

Based in Maseru KB Office

Duties and Responsibilities

Position Overview

A Data Scientist will be responsible for drawing value out of data. He/She proactively fetches information from various sources and analyse it for better understanding about how the program performs, and builds Artificial Intelligence tools that automate data cleaning, validation to ensure data uniformity and accuracy.

Responsibilities include, but are not limited to the following:

  • Work as the lead data strategist, identifying and integrating new datasets that can be leveraged through our product capabilities and work closely with the Strategic information team to strategize and executive the development of data products;
  • Identify relevant data sources and sets to mine for programmatic needs and collect large structure and unstructured datasets and variables;
  • Devise and utilize algorithms and models to mine big data stores, perform data and error analysis to improve models, and clean and validate data for uniformity and accuracy;
  • Analyze data for trends and patterns, and interpret data with a clear objective in mind;
  • Implement analytical models into production by collaborating with software developers

Educational Qualifications, Work Experience and Key Competencies

  • Bachelor’s degree in statistics, applied mathematics, Data Sciences Information Systems or related discipline;
  • 3+ years’ experience in data science;
  • Proficiency with data mining, mathematics, and statistical analysis;
  • Advanced pattern recognition and predictive modelling experience;
  • Experience with Advanced Excel, PowerPoint,  Power BI, Tableau, SQL, DHIS 2 and programming languages (i.e., Java/Python, SAS);
  • Comfort working in a dynamic, research-oriented group with several on-going concurrent projects;
  • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks;
  • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications;

Highly qualified Citizens and Residents of Lesotho are strongly encouraged to apply.

How to apply:  Interested candidates who meet the criteria must email applications letters including CVs showing three work-related referees with contact details (one should be from current supervisor/employer), certified copies of educational certificates, identity documents.

All applications must be emailed to [email protected] on or before Friday, 18th February 2022. Clearly indicate the name of the post applied for on the subject Line. Applications to be submitted through the email provided only. No hard copies will be accepted. Late applications will not be considered. Failure to comply with the above directions will results in the application being disqualified.

BCMCFL reserves the right to leave an advertised position unfilled if no suitable candidate is identified. Only shortlisted candidates will be contacted.

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