Retention & LTV Decision Scientist

Bioma – probiotic supplements designed to support gut health, energy levels, and focus by replenishing good gut bacteria.

As a Retention & LTV Decision Scientist, you’ll turn open business questions into clear, trustworthy answers that change our retention, subscription, and lifetime-value decisions – framing the right question, knowing when an answer can be trusted, and turning it into a recommendation people act on, using AI to move fast on the rest. You’ll read from our data marts, work with the Analytics Lead and partner with the Analytics Engineer on what’s worth modelling and why.

Get ready to

• Take ambiguous retention questions, structure them, and decide the fastest credible way to an answer – ad-hoc deep-dive, experiment, dashboard, or recurring analysis – without getting stuck in analysis paralysis.
• Run retention and churn diagnostics across plans, cycles, and sources to explain what’s driving customer loss.
• Build churn models and define lifecycle stages and actionable segments to inform interventions.
• Distinguish voluntary from involuntary churn so the business understands the difference between customers we lose and customers who choose to leave.
• Build cohort lifetime-value analysis and map customer journeys to their realised and predicted value.
• Design and measure retention initiatives through A/B and hold-out experiments, applying sound statistical and causal methods.
• Analyse the drivers of cancellations, refunds, and payment failures to inform recovery efforts.
• You’re expected to use AI to do routine querying, analysis, and reporting fast – so your time goes to framing, judgment, and verifying what’s correct, not manual production.
• Deliver proactive, recurring retention insight readouts – and help non-technical teams self-serve answers.
• Own your recommendations end-to-end: translate findings into decisions growth and operations stakeholders act on, stand behind them, and flag tracking gaps.

• BSc/MSc in statistics, mathematics, econometrics, economics, or a related field – or equivalent practical experience.
• 2+ years in decision science, analytics, or a quantitative subscription/retention role, balancing depth of analysis with business impact.
• Strong problem framing and judgment: able to challenge unclear requests, design robust metrics, and know when a result is trustworthy.
• Knowledge of statistical and causal methods – regression, hypothesis testing, experimentation, hold-out measurement, and inferential techniques.
• Strong SQL and Python for analysis, modeling, and automation; fluency with BI tools (e.g. Looker).
• AI-native ways of working: using AI to accelerate execution while applying your own judgment to the output.
• Solid grasp of subscription and retention concepts: churn, cohorts, lifetime value, and voluntary vs. involuntary loss.
• A strong communicator who can present complex findings clearly and persuasively to technical and non-technical audiences.
• Curious, results-oriented, and comfortable with iterative work in a small, fast-moving team.
• Fluent English, written and spoken.

Nice to have

• Bonus: experience in customer lifecycle management or predictive LTV modeling.

• Gross salary range is 3500- 5000 EUR/month.
• For Vilnius: 4 days onsite, 1 flexible day remote. Meanwhile, in Kaunas, remote options are available depending on the role.
• Health insurance (after probation), on-site physiotherapist, office gym, and fitness classes.
• 7 extra days off, 3 for weddings, hybrid work, and the freedom to work 2 months from anywhere in the world.
• Pet-friendly office, fresh breakfasts, hot lunches, drawers and fridges stocked with snacks and food.
• Rooftop and cellar events, 10 social clubs.
• Public transport card for Vilnius and Perks.lt perks.
• €1100 yearly budget for coaching, mentorship, training, conferences, online courses, subscriptions, books.
• €1500 for every successful referral.