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Data Analyst - First Data Hire

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Data Analyst - First Data Hire

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.

What You'll Do

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

What We're Looking For

Technical Expertise

  • 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

Experience & Background

  • 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

Mindset & Collaboration

  • 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 Have

  • 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

This position offers competitive compensation with equity, reflecting the high-impact nature of the role. If you're passionate about data, excited to build from scratch, and want to shape how a cutting-edge AI company measures and understands its impact, this role at Mem0 could be your next opportunity.

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