Job Title: Data Scientist – Bayesian & Clinical Analytics

Location: Ahmedabad, Gujarat

Job Type: Full Time

Department: Data Science / AI & Analytics

About Simform:

Simform is a premier digital engineering company specialising in Cloud, Data, AI/ML, and Experience Engineering to create seamless digital experiences and scalable products. Simform has strong capabilities across Microsoft, AWS, Google Cloud, and Databricks. With a presence in 6 countries, Simform primarily serves North America, the UK, and the Northern European market. Simform is well-recognised as one of the most reputed employers in the region, having created a thriving work culture with a high work-life balance that gives a sense of freedom and opportunity to grow.

Role & Responsibilities:

• Design, develop, and optimise Bayesian and probabilistic models for biological, clinical, and fertility-related datasets.

• Analyse complex physiological and time-series data to improve prediction accuracy, posterior inference, and scientific reliability.

• Evaluate existing probabilistic algorithms, scientific methodologies, and implementation approaches to identify evidence-based improvements.

• Collaborate closely with cross-functional teams including data scientists, software engineers, product teams, and clinical stakeholders.

• Conduct research and literature reviews in reproductive medicine, fertility science, and related clinical domains to support model development.

• Develop prototype-level implementations and validate algorithmic improvements using real-world datasets.

• Create technical and scientific documentation including research summaries, validation reports, model design documents, and analytical findings.

• Contribute to the development of innovative digital health and FemTech solutions with a strong focus on scientific accuracy and user impact.

• Support continuous improvement initiatives across data science workflows, experimentation, model validation, and research practices.

• Stay updated with emerging trends in Bayesian modelling, AI/ML, digital health technologies, and reproductive science.

Required Skills & Qualifications:

Algorithmic & Technical Skills — Essential

• Strong experience with Bayesian or probabilistic modelling applied to biological, healthcare, or clinical datasets.

• Expertise in posterior inference, prior specification, probabilistic reasoning, and time-series estimation techniques.

• Proficiency in Python and strong understanding of scientific computing ecosystems and existing analytical codebases.

• Ability to critically evaluate algorithms from both implementation and scientific perspectives and propose data-driven improvements.

• Experience working with statistical modelling, machine learning, and analytical problem-solving approaches.

Medical & Scientific Background — Good to Have

• Strong understanding of reproductive physiology including menstrual cycle dynamics, ovulation timing, luteal phase, and fertility science.

• Familiarity with fertility tracking methodologies and biomarker-based approaches such as basal body temperature and hormonal markers.

• Understanding of validation standards relevant to contraceptive and digital health applications, including Pearl Index methodology and regulatory considerations.

• Experience conducting literature reviews and synthesising clinical or scientific research findings.

Nice to Have

• Prior experience in the FemTech industry or cycle-tracking products.

• Exposure to digital health regulations or medical device development processes.

• Experience validating algorithmic improvements using real-world healthcare or clinical datasets.

Working Style

• Comfortable working independently on complex scientific or analytical codebases.

• Strong documentation and technical writing capabilities for both technical and non-technical audiences.

• Collaborative mindset with excellent communication and stakeholder interaction skills.

• Fluent in written and spoken English.

Educational Qualification

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Biomedical Engineering, Biotechnology, or a related field.

Why Join Us:

• Young Team, Thriving Culture

• Flat-hierarchical, friendly, engineering-oriented, and growth-focused culture.

• Well-balanced learning and growth opportunities.

• Free health insurance.

• Office facilities with a game zone, an in-office kitchen with affordable lunch service, and free snacks.

• Sponsorship for certifications/events and library service.

• Flexible work timing, leaves for life events, WFH, and hybrid options.