Qdrant

Technology, Information and Internet

51-200

United States

Qdrant is an open-source, high-performance AI search engine and vector database, designed to power AI-driven applications. Our technology helps developers build state-of-the-art semantic search, RAG, recommendation systems, and large-scale AI solutions.

We’re looking for a strategic Senior Data Scientist with a strong engineering focus and understanding of GTM to own and evolve our data infrastructure with a specific focus on the data warehouse, product analytics, and direct partnership with go-to-market (GTM) operations. This role will serve as a key bridge between Engineering, Product, Design and revenue teams, owning product analytics and ensuring that clean, accessible, and actionable data flows seamlessly from the data warehouse into our GTM systems.

The ideal candidate thrives at the intersection of engineering, analytics, and business strategy, and can drive measurable business impact through data.

## Tasks

*   **Own the Data Warehouse**: Maintain and optimize our centralized data warehouse (Snowflake), ensuring reliability, scalability, and data integrity across the business.
*   **Product Data Infrastructure**: Design and manage robust pipelines that capture and structure product usage data for downstream analysis and GTM use cases.
*   **GTM System Enablement**: Partner with GTM Operations to design and maintain data syncs from the warehouse into Salesforce, HubSpot, and other operational tools, supporting segmentation and automation.
*   **Reporting & Dashboards**: Build and maintain self-serve dashboards and custom reports in BI tool (Metabase) to empower stakeholders with accurate, timely insights.
*   **Drive Analytics Across PLG and PQL Motions**: Build visibility into activation journeys, usage health, key product signals, and retention metrics to identify product-qualified leads, inform growth strategies, improve user adoption, and strengthen long-term engagement. This requires a data scientist who can not only analyze and model the data but also design and maintain the underlying pipelines to ensure reliability and scale.
*   **Cross-functional Collaboration**: Partner closely with Product, Engineering, Sales, Marketing, and GTM Operations to understand data needs and deliver reliable solutions.
*   **Data Governance & Quality**: Implement best practices in data validation, documentation, and source-of-truth definition.
*   **Product Alerts**: Help with customer facing in-product alerting and recommendations based telemetry indicators.

## Requirements

*   5+ years of experience in data science, analytics engineering, or a similar role.
*   Strong understanding of PLG and PLS motions.
*   Deep proficiency in SQL and experience working with modern data stacks (dbt, Snowflake, Segment, etc.).
*   Demonstrated ability to work cross-functionally with GTM teams and translate business needs into scalable data solutions.
*   Looking to take ownership with strong builder mentality
*   Experience with Snowflake, Metabase, Segment, HubSpot, Salesforce, Mixpanel

## Benefits

*   Work at the cutting edge of vector search and AI infrastructure.
*   Be part of a fast-growing, well-funded startup with a vibrant open-source community.
*   Competitive salary and remote-friendly work environment.
*   A chance to be part of a rapidly growing company at the forefront of AI and vector search.

Employee

Professional / Experienced

<p>Qdrant is an open-source, high-performance AI search engine and vector database, designed to power AI-driven applications. Our technology helps developers build state-of-the-art semantic search, RAG, recommendation systems, and large-scale AI solutions.</p>
<p>We’re looking for a strategic Senior Data Scientist with a strong engineering focus and understanding of GTM to own and evolve our data infrastructure with a specific focus on the data warehouse, product analytics, and direct partnership with go-to-market (GTM) operations. This role will serve as a key bridge between Engineering, Product, Design and revenue teams, owning product analytics and ensuring that clean, accessible, and actionable data flows seamlessly from the data warehouse into our GTM systems.</p>
<p>The ideal candidate thrives at the intersection of engineering, analytics, and business strategy, and can drive measurable business impact through data.</p>
<h2 id="tasks">Tasks</h2>
<ul>
<li><strong>Own the Data Warehouse</strong>: Maintain and optimize our centralized data warehouse (Snowflake), ensuring reliability, scalability, and data integrity across the business.</li>
<li><strong>Product Data Infrastructure</strong>: Design and manage robust pipelines that capture and structure product usage data for downstream analysis and GTM use cases.</li>
<li><strong>GTM System Enablement</strong>: Partner with GTM Operations to design and maintain data syncs from the warehouse into Salesforce, HubSpot, and other operational tools, supporting segmentation and automation.</li>
<li><strong>Reporting &amp; Dashboards</strong>: Build and maintain self-serve dashboards and custom reports in BI tool (Metabase) to empower stakeholders with accurate, timely insights.</li>
<li><strong>Drive Analytics Across PLG and PQL Motions</strong>: Build visibility into activation journeys, usage health, key product signals, and retention metrics to identify product-qualified leads, inform growth strategies, improve user adoption, and strengthen long-term engagement. This requires a data scientist who can not only analyze and model the data but also design and maintain the underlying pipelines to ensure reliability and scale.</li>
<li><strong>Cross-functional Collaboration</strong>: Partner closely with Product, Engineering, Sales, Marketing, and GTM Operations to understand data needs and deliver reliable solutions.</li>
<li><strong>Data Governance &amp; Quality</strong>: Implement best practices in data validation, documentation, and source-of-truth definition.</li>
<li><strong>Product Alerts</strong>: Help with customer facing in-product alerting and recommendations based telemetry indicators.</li>
</ul>
<h2 id="requirements">Requirements</h2>
<ul>
<li>5+ years of experience in data science, analytics engineering, or a similar role.</li>
<li>Strong understanding of PLG and PLS motions.</li>
<li>Deep proficiency in SQL and experience working with modern data stacks (dbt, Snowflake, Segment, etc.).</li>
<li>Demonstrated ability to work cross-functionally with GTM teams and translate business needs into scalable data solutions.</li>
<li>Looking to take ownership with strong builder mentality</li>
<li>Experience with Snowflake, Metabase, Segment, HubSpot, Salesforce, Mixpanel</li>
</ul>
<h2 id="benefits">Benefits</h2>
<ul>
<li>Work at the cutting edge of vector search and AI infrastructure.</li>
<li>Be part of a fast-growing, well-funded startup with a vibrant open-source community.</li>
<li>Competitive salary and remote-friendly work environment.</li>
<li>A chance to be part of a rapidly growing company at the forefront of AI and vector search.</li>
</ul>


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