As a Data Scientist, you'll be at the intersection of product, growth, and AI - turning ambiguous business challenges into rigorous analytical solutions that shape how Aftershoot grows and retains its global user base. You'll own the full lifecycle: from scoping the right problem to building production-grade models to driving alignment with cross-functional stakeholders.

The Core Responsibilities For The Job Include The Following Problem Scoping and Analytics:

- Independently translate business questions from Product, Marketing, and Growth into well-defined analytical problem statements with minimal rework or scope creep.
- Own the end-to-end analytics lifecycle: from understanding the question to delivering an actionable recommendation.
- Build scenario planning models and strategic analyses that directly inform product roadmaps and commercial decisions (e. g., repricing segmentation, churn strategy, and seasonality planning).

Model Development And Deployment

- Build and deploy production-grade predictive models - such as churn probability scores at a user-month level - that are activated directly by downstream teams (e. g., marketing re-engagement campaigns).
- Develop likelihood models for key conversion events (e. g., Trial Conversion Likelihood / Trial Quality Index) using behavioural signals, engagement patterns, and user context.
- Build marketing spend optimisation models to improve ROI on paid acquisition channels.

Experimentation

- Own and roll out a rigorous A/B testing framework - covering experiment documentation, sample sizing, power analysis, guardrail metrics, significance testing, and a centralised results repository.





Communication And Stakeholder Management

- Present complex model outputs, analytical findings, and trade-offs in clear, non-technical language that enables confident decision-making by business stakeholders.
- Embed with OKR planning cycles and task prioritisation across Product, Marketing, and Growth to ensure data bandwidth is aligned with the highest-impact priorities.
- Manage stakeholder expectations on deliverables, timelines, and model limitations and drive projects through to organisational closure.

Requirements

- 3+ years of hands-on experience in data science, analytics, or a closely related role.
- Problem Scoping: Demonstrated ability to independently define analytical problems from ambiguous briefs, not just execute on pre-specified tasks.
- SQL (Advanced): Efficient joins, CTEs, window functions, and query optimisation for large datasets.
- Predictive Modelling: Proven experience building and deploying models (classification, regression, survival/churn) in a production workplace - not just in notebooks.
- Data Visualisation and Dashboarding: Strong experience building self-serve dashboards in Omni, Tableau, Power BI, Looker, or similar tools.
- Experimentation: Solid grasp of A/B testing methodology - power analysis, statistical significance, guardrail metrics, and experiment design.
- Communication: Ability to translate model outputs and analytical findings into business narratives that stakeholders can act on confidently.
- Analytical Thinking: Rigour in selecting the right methodology, questioning assumptions, and structuring a logical approach before execution.

This job was posted by Arushiy Dixit from Aftershoot.

📌 Data Scientist (Bawana)
🏢 Aftershoot
📍 Bawana