Data Analyst - First Data Hire

Mem0•San Francisco Bay Area, CA

About The Position

Mem0 is at the forefront of building the memory layer for AI agents, enabling artificial intelligence to remember conversations, learn from interactions, and build context over time. Already powering millions of AI interactions, the company is well-capitalized and backed by top-tier investors. As our first Data Analyst, you'll be responsible for building the data infrastructure and analytics foundation from scratch. You'll establish how we measure product performance, track key business metrics, and translate data into actionable insights that drive decision-making across the entire organization. This role requires expertise in SQL, data modeling, product analytics, and a unique ability to wear multiple hats—from data engineering to business intelligence to analytics tooling. The position demands a blend of technical depth and business acumen. You'll own the full spectrum of analytics: designing data pipelines from multiple sources (Postgres, PostHog, LLM outputs, and third-party APIs), building automated dashboards and reports, creating self-service analytics tools for stakeholders, and diving deep into data to uncover insights that inform product direction and business strategy. You'll work closely with Product, Engineering, and Leadership to define metrics that matter, establish measurement frameworks, and ship internal tools that scale with our growth. The role is based in Bangalore, India. Mem0's culture values extreme ownership, high trust, and data-driven decision-making. Team members are encouraged to take initiative and solve problems independently, while maintaining high standards for rigor and craftsmanship.

Requirements

Expert-level SQL skills with strong experience in PostgreSQL or similar relational databases
Proficiency in Python for data analysis, automation, and building data pipelines
Hands-on experience with product analytics platforms (PostHog, Mixpanel, Amplitude, or similar)
Proficiency with data visualization and BI tools (Tableau, Looker, Metabase, or similar)
Understanding of API integrations, data extraction, and ETL concepts
Familiarity with cloud platforms and modern data warehousing solutions
1-3 years of experience at growth-stage startups in data analysis, analytics engineering, or related roles
Prior experience as a first data hire or building analytics infrastructure from the ground up is strongly preferred
Demonstrated ability to work with diverse, unstructured data sources and complex data environments
Understanding of product development cycles and the ability to think like a builder, not just an analyst
Track record of moving fast and iterating in resource-constrained environments
Business acumen—you understand what insights actually matter and can translate data into actionable recommendations
Excellent communication skills; you can explain complex findings to both technical and non-technical stakeholders
Self-directed and comfortable navigating ambiguity; you identify problems and drive solutions independently
Adaptability and willingness to shift priorities and learn new tools as the company evolves
High ownership mentality; you care deeply about the quality and impact of your work

Nice To Haves

Experience with LLM data analysis, AI/ML workflows, or working with model outputs
Background in product management or strong intuition for product thinking
Knowledge of privacy-preserving data practices and data governance
Experience building evaluation frameworks for complex systems
Familiarity with experimentation platforms and statistical testing methodologies

Responsibilities

Data Infrastructure & Pipelines Build and maintain reliable data pipelines that consolidate information from Postgres databases, PostHog product analytics, LLM outputs, and external APIs into a unified data warehouse
Design data models and establish schemas that scale with our product and business needs
Implement data quality monitoring and validation processes to ensure accuracy and reliability
Set up automated ETL workflows and establish best practices for data collection and storage
Analytics & Insights Define and track key business and product metrics that measure our success (retention, usage, monetization, feature adoption, and more)
Build automated dashboards and reports for daily, weekly, and monthly business reviews
Conduct deep-dive analysis to surface trends, identify opportunities, and provide recommendations that influence product and business decisions
Support experimentation and A/B testing initiatives with analytical rigor and evaluation frameworks
Answer urgent, ad-hoc data questions from any part of the organization with speed and accuracy
Internal Tooling & Self-Service Develop internal tools and dashboards that enable non-technical stakeholders to access data independently
Create standardized reporting templates and processes that reduce repetitive requests
Build documentation and data definitions that keep the entire organization aligned on metrics and methodology
Train and support team members across the company on how to interpret and use data effectively
Cross-Functional Partnership Partner with Product to establish measurement frameworks and define success metrics for new features
Work with Engineering to ensure data collection is robust and metrics are accurate
Support Leadership and Go-to-Market teams with investor-ready analytics and strategic insights
Collaborate with Research on evaluation frameworks and hypotheses testing for memory and retrieval innovations