Job Description

About Lyra Health

Lyra Health is the leading provider of mental health solutions for employers supporting more than 20 million people globally. The company has delivered 13 million sessions of mental health care, published more than 20 peer-reviewed studies, and delivered unmatched outcomes in terms of access, clinical effectiveness and cost efficiency. Extensive peer-reviewed research confirms Lyra’s transformative care model helps people recover twice as fast and results in a 26% annual reduction in overall healthcare claims costs. Lyra is transforming access to life-changing mental health care through Lyra Empower, the only fully integrated, AI-powered platform combining the highest-quality care and technology solutions.

Role Overview:

We are searching for an experienced data scientist to be a technical partner in translating our deep domain expertise into statistically robust predictive models.

Remote: The role is fully remote to be based in South Africa

Hours: 8am to 5pm. The role is a permanent five (5) day a week role (Monday to Friday).

Flexibility: Given the global nature of the business, the successful candidate will be expected to demonstrate flexibility in their working hours and will be required to come into the office once a month (if Johannesburg based)

Key Responsibilities:

  • Predictive modelling (machine learning) - hands on experience building, validating and interpreting predictive models in Python.
  • Time-series analysis and forecasting - experience with models that analyse data over time to make a future prediction.
  • Applied statistical analysis - ability to test for the statistical significance of a trend.
  • Creative feature engineering - must be able to use thousands of individual data points into a handful of organisational level predictors.

Skills and Experience:

  • Advanced SQL - strong expertise in SQL, comfort with writing complex queries.
  • Collaborative ability to turn a hypothesis into a model - must have excellent listening and communication skills and be able to translate an intuitive hypothesis into a model.
  • Proven experience handling sensitive data - must understand the ethical implications of predictive modelling in mental health.

Requirements:

  • Advanced SQL & Data Architecture: Mastery of SQL with the ability to adapt queries across dialects (e.g., T-SQL to Snowflake).
  • Experience navigating complex relational databases to extract multi-modal datasets.

End-to-End Python Modelling: Hands-on experience using the Python data stack (Pandas, NumPy, Scikit-Learn) to build, validate, and deploy predictive models.

  • Forecasting & Time-Series Analysis: Expertise in analysing longitudinal data (data over time) using libraries like Prophet or Statsmodels to create forward-looking risk forecasts.
  • Creative Feature Engineering: A proven ability to transform messy, individual-level behavioural and clinical data into meaningful, aggregated organizational-level metrics.

Applied Statistics: Strong foundation in statistical significance testing, ensuring that discovered trends are mathematically sound and not just random noise.

  • Collaborative “Translator” Skills: Ability to bridge the gap between deep domain intuition and technical execution.
  • Must be able to explain complex model outputs to senior leadership and collaborate with Data Engineering to ensure model stability during warehouse migrations.
  • Data Ethics & Privacy: Experience working with sensitive clinical or wellbeing data, with a strict adherence to privacy standards (GDPR/POPIA/HIPAA) and anonymisation protocols.

In accordance with the Employment Equity Act, preference will be given to suitably qualified candidates from designated groups, including persons with disabilities.

“We are an Equal Opportunity Employer. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, age, disability, genetic information or any other category protected by law.

By applying for this position, you acknowledge that your personal information will be processed as per the Lyra Health Workforce Privacy Notice. Through this application, to the extent permitted by law, we will collect personal information from you including, but not limited to, your name, email address, gender identity, employment information, and phone number for the purposes of recruiting and assessing suitability, aptitude, skills, qualifications, and interests for employment with Lyra.  We may also collect information about your race, ethnicity, and sexual orientation, which is considered sensitive personal information under the California Privacy Rights Act (CPRA) and special category data under the UK and EU GDPR.  Providing this information is optional and completely voluntary, and if you provide it you consent to Lyra processing it for the purposes as described at the point of collection, for example for diversity and inclusion initiatives.  If you are a California resident and would like to limit how we use this information, please use the Limit the Use of My Sensitive Personal Information form.  This information will only be retained for as long as needed to fulfill the purposes for which it was collected, as described above. Please note that Lyra does not “sell” or “share” personal information as defined by the CPRA. Outside of the United States, for example in the EU, Switzerland and the UK, you may have the right to request access to, or a copy of, your personal information, including in a portable format; request that we delete your information from our systems; object to or restrict processing of your information; or correct inaccurate or outdated personal information in our systems. These rights may be subject to legal limitations. To exercise your data privacy rights outside of the United States, please contact [email protected]. For more information about how we use and retain your information, please see our Workforce Privacy Notice.”

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, summarizing interviews, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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