Head of DataHertility Health

Hertility is a women’s health company built by women, for women. We’re shaping the future of reproductive healthcare by pioneering unique diagnostic testing that provides data-driven and advanced insights into reproductive health, fertility decline and the onset of menopause. We provide expert advice, education and access to care - all from the comfort of your home.

31% of women will suffer from a reproductive health issue at some point and through our research, we aim to reduce the time to diagnosis through advanced at-home testing and specialist gynaecological care. We tailor pathways to the individual's reproductive goals, whether it be to explore their ovarian health and fertility options or overall hormonal health, such as confirming a PCOS diagnosis. Currently, we can diagnose 18 of the most common gynae pathologies which may lead to reduced fertility and signpost gynae cancers.

Ultimately, our aim is to change attitudes around reproductive health, both for individuals and in the workplace, and to encourage women to be proactive by tracking their reproductive health. We’re calling this the Reproductive Revolution!

The role

We're looking for a Head of Data to shape and execute our data strategy.

You’ll be leading our existing team of two, working closely with the wider business in owning all aspects of data collection, processing and analysis within the business.

The successful candidate will be responsible for creating a solid short, mid and long-term roadmap through to delivery.

Key responsibilities will include but not be limited to:

• Loving the power of data and can communicate its value to the whole business.
• Juggling between strategy, hands on coding and mentoring of the data team.
• Building a data function and leading a data team.
• Delivering data-driven solutions that support the company's growth and success.
• Implementing artificial intelligence and machine learning practices with a commercial goal.
• Working on data science problems which involve predictive analytics and forecasting.
• Understanding of modern data technologies, architectures, and best practices, including big data processing, data warehousing, and real-time analytics.
• Implementing robust data governance, ensuring data quality, security, and compliance with relevant regulations and industry standards.