Senior Data Analyst

**About mDoc**
At mDoc, we are transforming healthcare in underserved communities through AI-driven solutions that provide personalized support to individuals managing chronic conditions and regular health needs. Join us to build a platform that empowers lives and delivers impactful healthcare solutions.

**Role Overview**

**Key Responsibilities**
- **Data Collection & Analysis**:

- Gather, clean, and process large datasets from multiple sources, ensuring accuracy and consistency.
- Analyze trends, identify key performance indicators (KPIs), and provide data-driven insights to inform decision-making.
- Develop Python scripts for automation and data processing.
- Conduct exploratory data analysis (EDA) to identify patterns and correlations in data.
- **Data Visualization & Reporting**:

- Design and create interactive dashboards and reports using tools such as **Power BI, Tableau, Google Data Studio**, and **PostHog** to track business performance.
- Present findings to stakeholders in a clear and actionable manner.
- **Database & Query Optimization**:

- Write and optimize SQL queries to extract meaningful insights from databases.
- Work with **relational (SQL) and NoSQL databases** to support analytical needs.
- **Collaboration & Business Impact**:

- Partner with cross-functional teams to understand business and data needs to deliver insights that drive operational improvements.
- Support product and engineering teams in defining data requirements for new features and enhancements.
- **Quality Assurance & Compliance**:

- Ensure data integrity, governance, and compliance with industry standards (e.g., HIPAA, NDPR, GDPR).
- Implement best practices for data security and privacy.

**Qualifications**
- Bachelor’s degree in **Data Science, Statistics, Computer Science, or a related field**.
- **5 years** of experience in data analysis, reporting, or business intelligence.
- Strong proficiency in **Python** for data analysis
- Proficiency in **SQL** for querying databases and optimizing performance.
- Experience with **data visualization tools** (e.g., **Power BI, Tableau, Google Data Studio**).
- Basic understanding of statistical analysis, including hypothesis testing and regression modeling.
- Excellent analytical and communication skills, with the ability to interpret data and provide strategic recommendations.

**Preferred Skills**
- Experience with **Python or R** for data analysis and automation.
- Familiarity with **cloud-based analytics platforms** (e.g., AWS, GCP, Azure).
- Basic knowledge of **machine learning fundamentals** is a plus.
- Strong communication skills to present findings effectively to technical and non-technical stakeholders.

Pay: E£7,500.00 - E£22,000.00 per month

Application Question(s):

- A hospital partner wants to use predictive analytics to identify patients at high risk of chronic disease complications.

What types of data would you need to build a predictive model?
How would you handle data quality issues, such as missing or inconsistent records?
What machine learning techniques would you consider, and how would you evaluate the model’s effectiveness?
- You are analyzing a large healthcare database with millions of patient records. A report query that groups and aggregates patient visit data is running very slowly.

How would you identify and troubleshoot performance bottlenecks?
Can you provide an example of how you would rewrite or restructure a query for better performance?
- You have been asked to create a dashboard for tracking hospital readmission rates and patient engagement on mDoc’s platform.

What key metrics would you include, and why?
How would you ensure that the dashboard remains useful and actionable for clinical and operational teams?
What factors would you consider when choosing between different visualization techniques (e.g., bar charts, line graphs, heatmaps)?

**Experience**:

- Data: 5 years (required)