Data Specialist at mothers2mothers

Job Description

Over the last few years, starting with structural changes in client management tools and the introduction of digital health systems, m2m overhauled its entire routine SI system that drives programme performance management. In order to drive optimal access to, and utilisation of m2m digital data among a broad range of internal stakeholders, m2m is looking to employ a full-time Data Specialist. The purpose of this position is to support m2m’s Strategic Information function, situated within the Department of Programmes and Technical Support, through managing data and facilitating data access across multiple data sources and platforms; and through conducting data analytics and modelling as well as reporting & data utilisation, for improved programme management and optimal client outcomes.

Key Performance Areas: 

Managing Data Science, Machine Learning & Big Data: 

• Lead the data science team at DPTS and provide technical expertise on data analysis, sharing and data storytelling.
• Lead routine collation of relevant datasets from multiple internal and external sources, including undertaking pre-processing of structured and unstructured data to produce data products.
• Collaborate with country tripods, and country team to manage routine and ad hoc total data quality assurance practices to ensure optimal client outcomes.
• Lead the conceptualisation, planning, interpretation of and execution of data-focused problem-solving using analysis, modelling and ML approaches.

Lead the development and performance of bespoke data mining, wrangling & exploration models: 

• Lead the development & utilisation of predictive models and machine-learning algorithms to improve client outcomes and business processes.
• Lead routine updating of m2m’s ETL and EDA processes, including monthly reporting, BIO reporting, CQI analyses, APR and routine dashboards.
• Lead the use critical data analysis-analytics and investigative skills, as well as an ability to communicate findings, to mine vast amounts of data for insightful performance management insights, trend analysis, predictive modelling and identification of programmatic innovation and new implementation opportunities.

Supportive Supervision, Management and Capacity Building: 

• Lead the developing and documenting of the SI routine M&E system inclusive of, but not limited to the information pipeline, reporting schedule and reporting templates, routine M&E Tools, as well as Data Quality Audit tools and processes.
• Manage and support the development of SI/Data training materials, training of trainers & in-service training coordination at HO (e.g., manuals, PowerPoint slides, Job Aids, etc.).
• Manage the documentation, development, routine updating and maintenance of SI, data management and related tools in support of m2m and country teams
• Lead collaboration with HO and country teams to ensure innovative digital health solutions for m2m programmes are identified, modified, maintained and standardised.

Lead Data Science Project Management Approaches: 

• Lead the updating and maintenance of routine data science project management toolkit and templates.
• Manage the training, capacity building and process mapping of data science projects for m2m.
• Provide leadership and support for the initiation, planning, execution/monitoring and closure or completion of data science projects.
• Manage regular communication, updated documentation, scrum, Kanban or other lean methods to project management to all relevant stakeholders.
• Manage consultants and other external/internal stakeholders in support of data science projects.

Administration and business process management: 

• Keep a re-useable and clearly documented process for all data science tools steps, activities and materials.
• Ensure all data analysis/analytics is aligned with updated programme & info-tech guidelines and data quality metrics are improved continuously.
• Support maintenance of data products and presenting ad-hoc findings to DPTS.
• Clear, consider and regular communication of data science projects and activities to all stakeholders.

Job Requirements

 Qualifications and Experience:

• An Honours/Master’s Degree in a relevant field such as Mathematics, Statistics, Computer Science, Engineering, Data Science, Social Science, Business Science, Health Science or another quantitative field is preferred.
• Minimum of 7 years’ experience as a Data Specialist / Data Analyst / Data Scientist / Research Analyst applied in a quantitative field of analysis. Development experience is a plus.
• Experience in working in a HealthCare and Development context, in resource constrained settings
• Proven experience in data analysis, database querying, data mining, data analytics, reporting and effectively communicating data to stakeholders.
• Understanding of or experience with data visualisations & machine learning is a strong recommendation.
• Experience in using python, SQL, R or a similar statistical tool is a must, cloud experience is desired.
• Experience using business intelligence tools (e.g., Tableau) and data frameworks (e.g. Hadoop, XML, JSON, JavaScript) is a strong recommendation.
• Experience in using R, SQL and Python, Cloud Technology (GCP); familiarity with Scala, Visual Studio, Java or C++ is an asset. 
• Strong experience in time management, team management and leadership acumen
• Strong experience in analysing and managing risk and problem solving
• Strong communication skills, attention to detail and the ability negotiate and resolve conflict

Competencies:

• Highly analytical with an aptitude for data analysis, mathematics and statistics.
• Innovative, critical thinking.
• Data utilisation, storytelling and visualisation.
• Problem-solving / investigative skills.
• Passion for predicting trends and identifying patterns.
• Passion for research and machine-learning.
• The ability to work independently with minimal supervision.
• The ability to lead and manage a team in a fast-paced environment
• Excellent data storytelling and strategic skills