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mDoc
This is a remote position.
About mDoc
mDoc is digital health social enterprise that leverages behavioral science, technology and
quality improvement methodologies to provide improve access to quality healthcare for
people with chronic health needs. We are seeking knowledgeable health coaches to join our
team. Our goal is to augment the knowledge and capability of healthcare providers and health
consumers to ensure longer, happier and healthier lives across sub-Saharan Africa. mDoc aims
to further build capability and to support physicians to provide education and tools to patients
to improve self-management. Our ethos is etched in the belief that augmenting the healthcare
& technology landscape is paramount to helping Africa unlock its true potential. We are on a
mission to transform how African healthcare consumers receive the support they need to live
longer, healthier, happier and more productive lives.
Job Description:
We are seeking a enquiring, precise data analyst to contribute to the design and build of
analytic solutions that will inform business decisions, drive operations, measure our
performance and validate our value as a company. Healthcare data is complex and vast, so you
must be excited about sinking your teeth into complex problems, untangling them and
communicating your findings to the team. Behind every data element is a real person, with real
problems that mDoc is working hard to address, and the Data team is responsible for
delivering accurate and timely information to steer these efforts.
If you like hard problems, have experience pulling insight out of complex structured and
unstructured data sources, and are an amazing teammate, we want to hear from you!
Responsibilities
Collect, clean, and process large, complex datasets from multiple sources while ensuring data accuracy and consistency.
Write, optimize, and automate MongoDB queries to efficiently extract and process large datasets.
Develop Python scripts for automating the end-to-end ETL process.
Perform in-depth exploratory data analysis to uncover insights, trends, and anomalies.
Perform statistical analyses, including hypothesis testing, significance testing, and A/B testing to validate insights.
Utilize statistical and analytical techniques such as regression modeling, clustering, trend analysis, and time-series forecasting to generate actionable insights.
Apply Natural Language Processing (NLP) techniques to extract insights from unstructured text data.
Develop advanced dashboards and reports using Power BI, Tableau, Google Data Studio, and PostHog to track business performance.
Lead data review meetings to assess member health outcomes, evaluate coaching performance and impact metrics, and present evidence-based insights to key stakeholders in a clear, actionable manner.
Collaborate cross-functionally to define metrics, align business needs, and drive data-driven initiatives.
Support product and engineering teams in defining data requirements for new features.
Lead and contribute to high-quality research, abstracts, and publications.
Work with leadership to set OKRs, define priorities, and oversee project execution.
Mentor junior analysts share best practices, and support team growth.
Ensure compliance with industry regulations (e.g., HIPAA, NDPR, GDPR).
Ensure best practices for data security, privacy, and ethical data usage.
Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field.
4+ years of experience in Python for data analysis, automation, and statistical modeling.
Querying, optimizing, and managing large datasets from SQL and MongoDB databases.
Strong experience with data visualization tools (e.g., Power BI, Tableau, Google Data Studio).
Deep understanding of statistical analysis, including hypothesis testing, regression modeling, clustering, trend analysis, and time-series forecasting.
Strong experience in NLP for text analytics and sentiment analysis.
Knowledge of cloud-based analytics platforms (AWS, GCP, Azure).
Excellent problem-solving, analytical, and communication skills, with the ability to drive data-driven business decisions.
Strong leadership capability, with the ability to take initiative and drive the operations of the data team ensuring data accuracy, consistency, and reliability throughout the reporting process.
