Research Data Scientist (Wearables & Health Analytics)

Population lives in local calendar time. Each person lives on their biological time.

Actogram is built to measure their synchronisation.

Actogram is a circadian analytics company developing algorithms that transform wearable sensor data into meaningful indicators of biological rhythms, sleep-wake behavior, and long-term health. Analysis of population-scale datasets gives us clues on individual and populational rhythms synchronisation.

Our solutions are designed for wearable manufacturers, watch brands, digital health platforms, researchers, and longevity-focused applications.

Learn more about Actogram: https://actogram.watch/

We are currently expanding both our scientific research program and commercial product development.

We are looking for a junior+/middle/middle+ Data Scientist to analyze time-series data from fitness trackers: steps, sleep, heart rate, and other wearable signals.

Main tasks

— analyze wearable time-series data, including activity, sleep, heart rate;

— search for, evaluate, prepare, and analyze open-access wearable datasets;

— improve and validate sleep-wake and day/night labeling algorithms on real-world datasets;

— develop and optimise algorithms for modelling rest-activity cycles;

— develop interpretable algorithms (rather than deep-learning-first solutions);

— collaborate on scientific publications, technical documentation, and internal research reports;

— potentially participate in preparing materials for patents.

Required skills

— Git, Python (NumPy, SciPy, Pandas, Scikit-Learn);

— experience cleaning and preprocessing real-world datasets;

— understanding of statistical inference and hypothesis testing;

— ability to work with noisy, incomplete, or imperfect data;

— familiarity with signal-processing concepts is a plus.

Other tools can be learned during the work process, including with the help of an AI code assistant.

Nice to have

— experience with wearable data / fitness tracker data;

— a hobby project or Kaggle challenge with similar datasets;

— experience with sleep, activity, heart rate, or accelerometer data;

— experience working with open scientific or medical datasets;

— interest in circadian science, longevity, sleep science, or digital health;

— experience contributing to scientific publications or research projects.

What We Value

We care more about analytical thinking, curiosity, and practical problem-solving than formal years of experience.

The ideal candidate enjoys exploring unfamiliar datasets, reading scientific literature, testing ideas, and turning research concepts into working algorithms. We value people who can work independently, communicate clearly, and make progress in situations where the answer is not yet known.

Experience with wearable data is a strong advantage, but candidates from adjacent domains are encouraged to apply if they have a solid foundation in data analysis and a genuine interest in research.

Format

— Full-time;

— Remote;

— Salary starts from $3,000/month. Final offer depends on experience, skills, and interview results;

— Preferred geography: EU / UK;

— Technical interview will be conducted by the project lead.

English is needed for communication, reading scientific materials, working with datasets, and contributing to the preparation of a scientific paper.