Our B2B flagship platforms ELSA Enterprise and ELSA Schools empower organizations and educational institutions to elevate communication capabilities and unlock personal and professional opportunities for their people. We design engaging, bite-sized learning experiences that adapt to each learners goals and context, ensuring measurable improvement and lasting confidence.

Our vision is to become the global standard for real-time English communication training, enabling 1.5 billion language learners worldwide to speak clearly, be understood, and share their stories with the world.

Backed by world-class investors including Googles Gradient Ventures, Monks Hill Ventures, and SOSV, ELSA has been recognized among the top global AI innovators:

• Forbes Top 4 Companies Using AI to Transform the World
• Research Sniper Top 5 Best AI Apps
• ASU+GSV EdTech 150
• CB Insights Top 100 AI Companies

Join us in shaping the future of language learning and empowering millions to unlock opportunity through confident communication.

Job overview:

We're seeking a Senior Data Scientist to drive product and growth analytics for ELSA's rapidly scaling consumer and enterprise products. You'll work cross-functionally with Product, Engineering, Marketing, and Business Development teams to uncover insights that shape product strategy, optimize user experience, and accelerate growth. This is a high-impact individual contributor role where your analyses will directly influence decisions affecting millions of users and multi-million dollar revenue streams.

Key Responsibilities

Product Analytics (50%)

• Funnel Optimization: Analyze user journeys from acquisition through activation, engagement, retention, and monetization
• Feature Impact: Design and evaluate A/B tests for new product features, measuring impact on key metrics (retention, engagement, conversion)
• User Segmentation: Build cohort analyses to understand behavior patterns across user segments, geographies, and subscription tiers
• Churn Prevention: Identify early warning signals for churn and work with Product to build interventions
• Product Insights: Conduct deep-dives on user behavior to answer questions like:
• Why do users in Japan have 2x higher retention than other markets?
• Which lesson types drive the most engagement and subscription conversions?
• What's the optimal free trial duration to maximize LTV?

Growth Analytics (30%)

• Channel Performance: Analyze marketing channel efficiency (CAC, ROAS, payback period) across paid and organic channels
• Conversion Optimization: Build models to improve conversion at each stage of the funnel (install → trial → paid)
• LTV Modeling: Develop predictive models for customer lifetime value across different cohorts and acquisition channels
• Pricing & Monetization: Analyze pricing experiments, subscription tier performance, and revenue optimization opportunities
• Attribution: Build multi-touch attribution models to understand the customer acquisition journey

Analytics Infrastructure & Enablement (20%)

• Dashboard Development: Build self-service dashboards and reports for Product, Growth, and Leadership teams
• Data Models: Create reusable SQL views, dbt models, and data transformations for common analytics use cases
• Metric Definition: Establish clear definitions and tracking for core KPIs (DAU, MAU, retention curves, NPS, etc.)
• Documentation: Maintain analytics playbooks and best practices for the team

What You Will Have

Must-Haves:

• 4-6 years of experience in data science, analytics, or related roles (product analytics, growth analytics, business intelligence)
• Strong SQL skills - you can write complex queries with CTEs, window functions, joins, and subqueries to extract insights from large datasets
• Python or R proficiency for data analysis, visualization, and statistical modeling (pandas, matplotlib, scikit-learn)
• A/B Testing Expertise - you understand experimental design, statistical significance, power analysis, and common pitfalls
• Product Analytics Experience - you've worked on consumer products and understand funnel metrics, retention curves, and cohort analysis
• Statistical Foundation - comfortable with hypothesis testing, regression analysis, and basic predictive modeling
• Business Acumen - you can translate technical findings into actionable recommendations for non-technical stakeholders
• Communication Skills - you've presented insights to product managers, engineers, and leadership teams

Strongly Preferred:

• Experience with SaaS/subscription business models and understanding of metrics like MRR, ARR, churn, expansion revenue
• Background in mobile app analytics (iOS/Android) or EdTech products
• Familiarity with analytics tools: Amplitude, Mixpanel, Google Analytics, Tableau, Looker, or Metabase
• Experience with modern data warehouses: Snowflake, BigQuery, or Redshift
• Knowledge of dbt (data build tool) for data transformation and modeling
• Understanding of marketing analytics: CAC/LTV, attribution, channel optimization
• Experience analyzing APAC markets and understanding regional user behavior differences

Nice-to-Have:

• Bachelor's or Master's degree in Statistics, Mathematics, Economics, Computer Science, Engineering, or related quantitative field
• Experience with machine learning for classification, clustering, or recommendation problems
• Knowledge of causal inference techniques (propensity score matching, difference-in-differences)
• Contributions to analytics blogs, open-source projects, or Kaggle competitions
• Experience with data visualization tools like Tableau, Looker, or Superset

Who You Are

• Intellectually Curious: You love digging into data to understand the "why" behind user behavior
• Action-Oriented: You don't just find insights - you work with stakeholders to turn them into action
• Self-Starter: You identify opportunities proactively and don't wait to be told what to analyze
• Pragmatic: You balance analytical rigor with speed, knowing when "good enough" beats "perfect"
• Collaborative: You work well with cross-functional teams and can translate between technical and business language
• Detail-Oriented: You catch data quality issues and ensure your analyses are accurate and reproducible
• Growth Mindset: You're eager to learn new techniques, tools, and domains

What We Offer

• Flexible Work Setup: Remote-first in India and a hybrid model in Vietnam to support both flexibility and collaboration.
• Comprehensive Well-Being Benefits: A benefits package designed to support your physical, mental, and financial health.
• Free ELSA Premium Access: Complimentary access to ELSA Premium to continuously strengthen your English communication skills.
• Global Impact at Scale: Your analyses will directly improve the learning experience of millions of users worldwide.
• Rich, Global Data: Work with large, diverse datasets spanning 100+ countries, multiple platforms, and varied user segments.
• Modern Data Stack: Gain hands-on experience with tools such as Snowflake, dbt, and Amplitude while solving complex analytical problems.
• Cross-Functional Collaboration: Partner closely with Product, Engineering, Marketing, and Business teams to drive data-informed decisions.
• Clear Career Progression: Defined pathways to senior and specialized roles such as Staff Data Scientist, Growth Lead, or Product Analytics Lead.