Senior Statistician

[Note, job location can be Cambridge, Brighton, Mix or Hybrid]

Join health-equity.ai as a Senior Statistician / Data Scientist and spearhead our mission to transform healthcare data into actionable insights. With a minimum of 2-3 years of experience or post PhD, you’ll lead end-to-end data science projects, ensuring accuracy and integrity at every stage, from data collection to insight dissemination.

Health-equity.ai stands at the intersection of healthcare and artificial intelligence, embodying a commitment to ensure that every individual, regardless of their background, has access to quality healthcare. This innovative organization leverages the power of AI to analyse extensive health data, uncovering patterns of disparities and crafting targeted interventions to bridge the gap in healthcare equity.

The mission of health-equity.ai is rooted in the belief that healthcare is a fundamental human right, not a privilege. By harnessing advanced analytics and machine learning, health-equity.ai aims to provide insights that lead to more informed decisions, better health outcomes, and the elimination of systemic barriers to care. Their work focuses on identifying and addressing inequities in healthcare delivery, from the diagnosis to the accessibility of cutting-edge treatments.

health-equity.ai’s vision extends beyond mere analysis; it is about action and impact. The organisation’s AI-driven approach is designed to empower healthcare providers and policymakers with the tools they need to make data-driven decisions that promote health equity.

Responsibilities:

• Understanding of end to end data projects and implementing pipelines
• Lead and manage a small team of data scientists.
• Oversee the full lifecycle of data science projects, from data collection to dissemination.
• Perform advanced statistical analysis and machine learning to drive project success.
• Translate complex datasets into clear, actionable insights for stakeholders.
• Develop impactful visualizations and reports to communicate findings.
• Collaborate with cross-functional teams to integrate data science into broader company initiatives.
• Validate all processes and project insights to ensure the highest level of accuracy.

Must-Have Skills:

• Fluent Statistics
• Proficiency in Python
• Experience with ML packages such as scikit-learn and xgboost.
• Deep understanding of common ML algorithms
• Expertise in data handling, cleaning, and analysis using tools like pandas and NumPy.
• Advanced data visualization skills with Matplotlib, Seaborn, or Plotly.
• Familiarity with database systems and SQL.
• Proficiency with Excel, PowerPoint, Jupyter Notebooks, and IDEs like Pycharm or Visual Studio.

Nice-to-Have Skills:

• Experience with version control systems like Git/Github.
• Experience with dashboard tools such as Streamlit.
• Knowledge of deep learning frameworks like Pytorch and TensorFlow.
• Quick learner, especially in healthcare data contexts.
• Experience with cloud technologies such as AWS.
• Proficiency in Linux and shell scripting.

Essential Qualities:

• Meticulous attention to detail.
• Strong collaboration and communication skills.
• Fluent in English, with outstanding verbal and written communication capabilities.