---
title: 'Data Scientist at Valerie Group'
canonical: 'https://feeny.ai/job/data-scientist-valerie-group-bengaluru-6eqsf2wnjmjz'
type: 'job'
last_seen: '2026-10-15'
---

# Data Scientist at Valerie Group

- **Company:** Valerie Group
- **Location:** Bengaluru, India
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-10-06
- **Last confirmed live:** 2026-10-15
- **Apply:** https://jobs.ashbyhq.com/valerie-group/e5fba810-40de-4234-b216-6c37c6b9c5bf

## Job description

## About the Role

We are hiring a Data Analyst / Data Scientist to drive growth, commercial and product analytics, applied data science, and AI-driven capabilities across Valerie's Brands and Investment Growth Platform. In this role, you will work across product analytics, modeling, experimentation, and data workflows, using SQL and Python to turn complex business and product questions into actionable insights and production-ready analytical solutions. You will collaborate closely with Product, Engineering, and Data teams to operationalize models, shape how AI and model outputs are integrated into the product, validate model-driven decisions, and build data systems that continuously enhance product and commercial performance.

## Key Accountabilities

1. Product Analytics & Insights

- Define and track key product metrics, including user behavior, funnels, drop-offs, and feature performance.
- Translate complex product questions into structured analysis and actionable recommendations that directly influence product, growth, commercial, or investment decisions.

1. Applied Data Science & Modeling

- Build and apply models for segmentation, scoring systems, classification, and recommendations, ensuring alignment with product use cases and practical deployment.
- Partner with Engineering and Data teams to operationalize models and analytical workflows to ensure production-grade reliability.
- Work effectively with incomplete, imperfect, or banded data—making assumptions explicit and identifying gaps that materially affect analysis or decision-making.
- Own analytical and modeling projects end-to-end: from defining the business problem and data requirements through modeling, validation, deployment, and impact measurement.
- Build and apply forecasting, unit economics, scoring, incrementality, media effectiveness, or other decision models relevant to commercial and product use cases.

1. Experimentation & Testing

- Design and run experiments, including A/B testing and cohort analysis.
- Measure the impact of product changes, AI outputs, and workflow adjustments.
- Build feedback loops to continuously improve product and model performance over time.
- Quantify uncertainty, test assumptions, and clearly communicate the limitations and confidence levels of analytical conclusions.

1. Data Infrastructure & Quality

- Define data requirements for new product features and ensure data tracking is accurate, consistent, and complete.
- Collaborate with engineering to structure datasets and pipelines for analysis and modeling.
- Identify and resolve gaps in data visibility.

Ideal Background & Qualifications

- Experience: 6–8 years of relevant analytics or data science experience, with demonstrated ownership of meaningful analytical or modeling work.
- Problem-Solving: Strong ability to translate ambiguous business, product, growth, or commercial problems into structured data questions and actionable analytical approaches.
- Domain Knowledge: Experience working with product metrics, funnels, and user behavior analysis. Experience in growth, DTC/e-commerce, marketplace, subscription, ad-tech, agency, or unit-economics-driven environments is preferred.
- Modeling Expertise: Experience building and applying classification, regression, clustering, scoring, forecasting, and decision systems, with evidence of taking at least one meaningful model or analytical product into real business use.
- Commercial Acumen: Strong understanding of growth and commercial metrics (CAC, AOV, COGS, contribution margin, payback period, breakeven) to inform business decisions.
- Technical Stack:
- Strong SQL skills.
- Experience with structured and semi-structured data.
- Strong working proficiency in Python for data analysis, modeling, experimentation, and automation (R experience is acceptable if backed by equivalent analytics capability).
- Proficiency with libraries such as pandas, NumPy, and scikit-learn.
- Experimentation & AI: Experience with A/B testing, statistical analysis, measurement, causality, and impact evaluation. Experience evaluating LLM/AI-generated outputs in product workflows (understanding response structures, quality, consistency, and reliability).
- Nice-to-Haves:
- Exposure to data visualization tools (Tableau, Power BI, Metabase).
- Experience in zero-to-one startup environments.
- Experience with media mix modeling, incrementality, causal inference, experimental design, or media effectiveness measurement.
- Experience with modern cloud data warehouses/workflows (Snowflake, BigQuery, dbt) and attribution platforms (Triple Whale, Northbeam, Rockerbox).
- Experience applying machine learning models in production.

What Success Looks Like (KPIs)

- AI & Integration: AI outputs are reliably interpreted and integrated into product workflows.
- Data-Driven Decisions: Product decisions are consistently backed by clear, actionable data insights.
- Operationalization: Analytical and models are successfully deployed and actively used in product, growth, or commercial workflows.
- Measurable Impact: Work delivers measurable improvements in product performance, growth, commercial outcomes, or decision quality.
- Experimentation: Experiments lead to measurable enhancements in product performance.
- Data Robustness: Data tracking and pipelines are robust, and quality gaps are identified and addressed early.
- Cross-Functional Alignment: Product, Engineering, and Data teams maintain clear alignment on data requirements, model outputs, and operationalisation.

Values We take our values very seriously and ask that all team members reference (or keep in mind) values in dealing with conflict, challenges, opportunities and day-to-day operations. Each individual's role is to also hold others accountable and themselves.

- Accountability- own your part in it first.
- Collaboration- take initiative with discipline and humility.
- Resilience- to be steadfast, assess, and bounce back.
- Selflessness- ‘what does it take to scale’.
- Fun- be present and connect.

The best time to join Valerie was yesterday. The next best time is now 🤓 👋Our Hiring Process We want interviews to be valuable for both sides. Throughout the process, you'll meet the people you'll work with, learn more about the role, and get a chance to understand how we think and operate. Our process typically includes:

- Introductory conversation with our Talent team <> 30 mins
- Hiring Manager interview <> 30-45 mins
- Role-specific assessment or practical exercise (where applicable)
- Cross-functional or stakeholder interviews <> 30-45 mins
- Final conversation with leadership <> 30-45 mins

We'll always let you know what to expect before each stage. 💪🏾What You Can Expect

- Meaningful work with visible impact
- High ownership from day one
- Collaboration with experienced founders, operators, and specialists
- A team that values curiosity, initiative, and continuous improvement
- Competitive compensation and the tools you need to do your best work
- Opportunities to grow as Valerie grows

Valerie is committed to building an inclusive workplace where people from different backgrounds, experiences, and perspectives can thrive. We hire based on skills, potential, and the ability to contribute to our team.

## About Valerie Group

## Company Overview
- **One-liner**: Valerie Group is an AI-driven growth and investment platform that partners with high-potential direct-to-consumer (DTC) e-commerce brands, providing technology, marketing services, and performance-based capital.
- **Entity Type**: Private (bootstrapped with performance-based funding; invitation-only)
- **Headquarters**: Singapore (68 Circular Road, #02-01, Singapore 049422)
- **Founded**: 2025
- **Founders**: Not publicly disclosed; leadership includes Stephen Doorey (Director)

## Core Business
- **Primary industry**: E-commerce growth infrastructure / AI-powered marketing services
- **Target customers**: DTC e-commerce brands (B2B, primarily small to mid-size with high potential)
- **Mission or purpose**: “To close the gap between what your brand is capable of and what it has been able to prove” — an equalizer for founders who deserve a level playing field.

## Products & Services
- **[Intelligence Platform](https://valeriegroup.com/)**: Proprietary AI that continuously processes market noise, audience behavior, and unit economics to surface high-ROI opportunities. Sold as a core component of the partnership.
- **[Service Engine](https://valeriegroup.com/)**: A unified team of elite specialists covering paid media, creative, CRO, email/SMS (Klaviyo), SEO, tech, and strategy. Operates on aggressive testing and outcomes-over-activity.
- **[Path to Funding](https://valeriegroup.com/)**: Performance-based capital deployment – equity is only taken after proof of value. Designed to avoid early dilution and align incentives with founder success.

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metric**: Total funding not disclosed; revenue not publicly available
- **Notable Investors/Partners**: None publicly listed; operates with its own capital and a partner fund
- **Growth Signals**: Headcount grew 425% year-over-year (to ~13 employees as of mid-2026); actively hiring 13+ roles across engineering, marketing, design, and operations; expanding remote presence across Singapore, Philippines, India, Australia, UK, UAE

## Competitive Advantages
- **Proprietary AI platform** built by e-commerce veterans – continuously scans 100,000+ brands to identify undervalued opportunities
- **Founder-friendly model** – no upfront equity or dilution; capital only deployed after validated performance
- **Invitation-only** – ruthless selection ensures high-conviction partnerships and elite operator culture
- **Unified execution** – replaces fragmented agency stacks with a single, aligned Service Engine

## Strategic Focus
- Scaling the number of high-potential DTC brand partnerships through continued AI model refinement
- Building out the autonomous Intelligence Platform to reduce manual effort while maintaining human strategic oversight
- Expanding global remote team (currently hiring for cloud infrastructure, creative, data, and project management roles)

## Why Work Here
- **Remote-first, high-autonomy culture** – “we don’t do corporate hierarchy” – emphasis on merit, performance, and skills over politics
- **Opportunity to earn ownership** in what you build, not just a salary
- **Work alongside world-class technologists, data scientists, and digital marketers** at the bleeding edge of e-commerce growth
- **Hybrid offices** in Bangalore, UK, and UAE; fully remote roles also available
- **Culture built for entrepreneurs** – “ruthless standard for craft and commitment” – ideal for those who want direct impact at a fast-growing startup

## Sources
1. [valeriegroup.com](https://valeriegroup.com/)
2. [jobs.ashbyhq.com (careers)](https://jobs.ashbyhq.com/valerie-group)
3. [builtin.com](https://builtin.com/company/valerie-group)
4. [sg.linkedin.com](https://sg.linkedin.com/company/valerie-group)
5. [remotefront.com](https://www.remotefront.com/companies/Valerie%20Group)

## Other roles at Valerie Group

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- [Email Marketing Manager](https://feeny.ai/job/email-marketing-manager-valerie-group-india-h45157znqf91) — India
- [Founding Cloud Infrastructure Engineer (AI Platform)](https://feeny.ai/job/founding-cloud-infrastructure-engineer-ai-platform-valerie-group-india-p6a432v10bct) — India
- [Digital Project Manager](https://feeny.ai/job/digital-project-manager-valerie-group-india-zfvr9pw8r22c) — India
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