Mimica is looking for a Senior/Lead Data Scientist/ML Engineer to join our ML Chapter and the Mapper team. You will own experiments and exploration of complex problems around task similarity and improving the use of the Mapper product, which creates intuitive flowcharts of user workflows.

What You'll Do

Design and run experiments to improve the ML processing system using classic and deep learning techniques.
Write clear technical reports documenting experiments and results.
Write clean, readable, and maintainable Python code, assuring best practices.
Interface with the internal Process Analyst team to discover automation opportunities, find pain points, and explore ML solutions.
Support productionization of ML models.
Actively collaborate in technical discussions with Engineers, Product Managers, and the ML Chapter to drive product development.
Contribute to knowledge sharing and process improvement.

What We're Looking For

Strong technical skills in setting up, running, and evaluating experiments using both classic and deep learning-based approaches.
Solid background in tabular data and event data classification.
A researcher mindset with curiosity and rigour in exploring and solving complex problems.
Ability to effectively mix classic and deep learning methods, with a clear understanding of when to apply each.
Proficiency in supervised and unsupervised learning techniques.
Excellent written communication skills, including the ability to produce clear and concise reports.
Strong Python programming skills, emphasising clear, readable code.
A drive to continually develop skills, improve team processes, and reduce technical debt.
Fluency in English, with the ability to effectively communicate abstract ideas, complex concepts, and trade-offs.

Nice to Have

Graph ML knowledge.
Experience designing, building and maintaining data pipelines.
Experience working in a high-impact, high-ambiguity startup environment, delivering value quickly and iteratively.

Technical Stack

Python

Team & Environment

You will be a member of the ML Chapter, working with the Mapper team. We prioritize customer needs first, work in small, project-based teams, and have flexibility in terms of the problems we work on. We own the full lifecycle of our projects, avoid silos, encourage taking up tasks in new areas, balance quality and velocity, have a shared responsibility for our production code, and each set our own routine to maximize productivity.

Benefits & Compensation

Generous compensation + stock options.
Distributed work: Work from anywhere - fully remote, in hubs, or a mix.
Company-issued laptop, remote setup stipend, and co-working budget.
Flexible schedules and location.
Ample paid time off, in addition to local public holidays.
Enhanced parental leave.
Health & retirement benefits.
Annual learning & development budget - up to £500 / €600 / $650 per year.
Annual workaways and regular virtual & in-person socials.
Opportunity to contribute to groundbreaking projects that shape the future of work.