We’re looking for a Data Scientist to take ownership of and develop our statistical modelling capabilities. You’ll work closely with our operations team to forecast orders and optimise efficient meeting of customer demand in our factory. You’ll also partner with the trading team to identify causal relationships between our proposition and customer satisfaction, and generate actionable insights to improve our fulfillment.
The role
Take ownership, develop and create data products to meet operational and commercial needs. You’ll be instrumental in the end‑to‑end data science lifecycle, from curating data sources through to operationalising models, working collaboratively with teams across data, engineering, operations and trading.
Your Responsibilities
* Operations & Finance – Order & Revenue forecasting
o Take ownership of our existing order and revenue forecasting capabilities, ensuring we operate efficiently in meeting factory demand.
* Trading – Customer Lifetime Value
o Partner with trading to identify key drivers of customer lifetime value.
o Through segmentation, predictive modelling and causal analysis generate actionable insights and recommend improvements.
* Trading & CRM – churn prediction
o Take ownership of existing churn models, assess performance and identify optimisation opportunities.
o Provide guidance on segmenting churn predictions across customer types and cohorts, and partner with stakeholders to use insights for retention.
* Ongoing model monitoring
o Collaborate with the analytics engineering team to develop a monitoring suite that reports on the health of models and quickly identifies aberrations.
The skills you’ll bring
* 2‑4+ years experience in a data science role, with a proven track record of deploying advanced statistical models in production.
* Highly desirable: a bachelor’s or master’s degree in a STEM field.
* Advanced proficiency in Python and SQL, with extensive experience in core data‑science libraries such as pandas/polars and scikit‑learn.
* Familiarity with cloud platforms (e.g. AWS) and orchestration tools (e.g. Airflow, Dagster) for operationalising data‑science products.
* Desirable: experience leveraging Snowflake AI/ML and robust data pipelines to deliver scalable, production‑ready solutions.
* Strong communication skills – able to translate technical insight into clear business recommendations for varied audiences.
* Highly competent time‑management skills, able to prioritise and deliver impactful work with key partners.
* Skilled in data visualisation and storytelling (e.g. ThoughtSpot, Looker, Tableau).
* Experience influencing cross‑functionally with product, proposition, engineering, R&D and data teams.
* Highly desirable: subscriptions business experience.
What’s in it for you?
* Competitive salary, reviewed annually.
* Flexible core hours for true work‑life balance.
* Hybrid role – 2 days in the London office.
* 25 days of holiday (excluding bank holidays), increasing to a maximum of 27 days.
* 9/10‑day fortnight to enhance wellbeing without pay reduction – over 20 additional days off in 2025.
* Optional 5 days unpaid leave and 1 paid volunteer day each year.
* Work from abroad 2 weeks every 6 months.
* Health insurance paid by Tails.com.
* Extended maternity, paternity, shared parental and adoption pay – 6 months at 70% pay.
* Flexible paid care leave for dependants and pets.
* In‑house L&D team with year‑round courses.
* 50% discount on all Tails.com products.
* Discounted gym membership.
What’s next?
If this matches your experience and what you’d love to do, we’d love to hear from you. If you’re unsure whether you exactly fit our criteria, please get in touch anyway. We especially welcome applicants from under‑represented demographics.
Our Commitment
We’re proud to be an active equal‑opportunity employer. We conduct a structured recruitment process for all candidates and actively promote our roles to communities that are under‑represented at Tails.com. During your interview process you’ll meet team members at varying levels of responsibility and experience. If you need reasonable adjustments, please let us know.
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