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Location
In office (Mumbai)
Seniority
Architect · 4+ years exp

First seen by Alion on Nov 5, 2026.

Overview
Company
Impact
Profile match
Traya combines dermatology, Ayurveda, and nutrition to build customised hair loss plans that target the root cause delivering assured results.

About Traya:

Traya is a health-tech company that treats hair loss end-to-end through a personalized program combining dermatology, Ayurveda, nutrition, and behavioral science.

We own the full pathway - assessment, regimen design, coaching, refills, and protocol adjustments - powered by an adherence engine and outcomes data that improve results over time.

We're not a cosmetic SKU brand or a marketplace; we set clear timelines, follow clinical governance, and focus on measurable outcomes.

Why This Role Exists:

Traya is rapidly evolving from product-market fit to profitable omnichannel growth (web, app, clinics, tele-coaching).

The winning edge lies in becoming a sharply data-driven organization - dramatically improving LTV, reducing CAC, boosting retention, and accelerating decision-making through data and AI.

The Head of Data Analytics will unite three critical functions i.e. Business Analytics, Data Science, and AI Evangelism into a high-impact growth engine that moves core business levers by double-digit percentages.

This is not about dashboards or models alone.

This is about owning outcomes and delivering measurable shifts in customer lifetime value, acquisition costs, retention, and operational excellence.

Your Mandate:

- Own the KPI Tree: Define, govern, and continuously refine Traya's measurement of growth, unit economics (LTV/CAC/payback/retention/funnel/ROI/NPS), and ensure a single source of truth.

- Be the Data Partner: Ground company strategy in evidence, challenge assumptions, and empower executives with trusted, real-time metrics for critical decisions.

- Run Data as a Product Org: Treat metrics, data pipelines, experiments, and ML models as scalable, monitored products with clear SLAs and ROI.

- Lead a Two-Pillar Team:

1. Analytics: Real-time insights, dashboards, experimentation culture.

2. Data Science: Advanced modeling including churn prediction, lead scoring, recommendations, forecasting, uplift models.

Key Outcomes to Deliver:

Retention Engine:

- Quantify CAC vs. LTV trade-offs by channel and cohort with actionable insights.

- Build churn prediction and adherence uplift frameworks.

- Establish incrementality testing to optimize marketing spend and trim waste.

- Define actions to improve customer adherence.

- Uplift studies and analysis.

Conversion & Experience Intelligence:

- End-to-end funnel analytics spanning acquisition to purchase, adherence, and repeat behavior.

- Standardize event tagging and governance across GA4, GTM, AppsFlyer, Branch, MoEngage, etc.

- Launch and govern a robust experimentation platform with clear guardrails.

Retail & Omnichannel Insights:

- Develop store potential and catchment area models to guide offline store expansion.

- Optimize offline assortment and store productivity through data scorecards.

- Integrate POS and CRM data for a unified customer view.

Advanced Analytics and ML in Production:

- Ship operational ML systems for scoring (churn, propensity), recommendations, and forecasting that directly link to revenue.

- Manage model retraining, monitoring, and robust MLOps pipelines.

Toolkit & Stacks:

- Technical Fluency: SQL, Python, BI tools (Looker/Tableau/PowerBI), scikit-learn/XGBoost, Spark/Flink, Airflow, Kafka/Kinesis, Snowflake/BigQuery, Trino.

- Business Context: Strong understanding of D2C or retail unit economics, customer cohorts, funnel dynamics, churn/LTV/CAC modeling.

- Growth Stack Exposure: GA4, GTM, AppsFlyer/Branch, MoEngage/Braze or equivalents.

Candidates we're looking for:

- 10 - 15+ years of progressive leadership in analytics, and data science, with at least 4 years leading integrated, multi-disciplinary teams.

- Proven track record of delivering measurable business impact improving LTV, reducing churn, shortening payback, and uplifting conversion funnels.

- Builder mindset: capable of architecting data platforms, yet willing to dive into SQL/Python code as needed.

- Operator and evangelist: raises organizational data IQ, creates self-serve analytics culture, and drives adoption rigorously.

- Exceptional storytelling ability, and a strong team player.

Location: Malad West, Mumbai (Work from Office)

Reporting to: Founder

Level: Functional Head

Skills

Data Science, Analytics, Data Analytics, Data Scientist, Marketing Analytics, Python, SQL, Statistics

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