Senior Data Scientist - Growth Marketing

Company Overview

Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people’s lives. With intelligent agreement management, Docusign unleashes business-critical data that is trapped inside of documents. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity. Using Docusign’s Intelligent Agreement Management platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e-signature and contract lifecycle management (CLM).

What you'll do

We're looking for a hands-on, execution-minded Lead Data Scientist to join Docusign's Marketing Measurement team. You will own the full range of data science and analytics work strategic analysis, experimentation, stakeholder insights while also building the modeled data layers, operational dashboards, analysis agents, and productized integrations that make measurement self-serve and scalable. In this high-impact position you will own the productization layer for marketing measurement, architecting data infrastructure that makes sophisticated methodology accessible at scale. You will independently drive complex cross-functional initiatives from definition through adoption. Over time you will extend these practices across the broader team, operating as an internal center of excellence for how we model, build, and ship data products. Our ideal candidate combines strong analytical foundations with a product mindset someone who thrives at the intersection of data modeling, data product design, and marketing measurement, with a bias for shipping working assets over polishing decks.

 

This position is an individual contributor role reporting to the Director, Marketing Data Science.

 

Responsibility

• Serve as DRI for measurement product initiatives end-to-end scoping, building, shipping, driving adoption across Marketing and Sales

• Architect and maintain the data modeling layer for marketing measurement clean, tested, documented models that the whole team builds on

• Productize measurement outputs into dashboards, automated reports, and analysis agents that stakeholders use without analyst intervention

• Push insights into end-user tools (CDPs, marketing platforms, CRM) so measurement drives action at the point of decision

• Partner with the pod's technical lead on methodology; translate attribution and incrementality science into production-grade data assets

• Define and enforce modeling standards (naming, testing, documentation) that scale across pods

• Collaborate with Data Engineering on pipeline reliability, orchestration, and upstream data quality

• Report regularly to executive stakeholders, surfacing measurement results with clear next steps

Job Designation

Hybrid: Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation)

 

Positions at Docusign are assigned a job designation of either In Office, Hybrid or Remote and are specific to the role/job. Preferred job designations are not guaranteed when changing positions within Docusign. Docusign reserves the right to change a position's job designation depending on business needs and as permitted by local law.

What you bring

Basic

• 8+ years of experience in analytics, data science, or marketing measurement

• Experience pulling insight from raw data and shipping durable models and products

• Experience with systems thinking, including how channels interact, where data flows break, and which upstream changes cascade downstream

• Experience writing sophisticated SQL, including well-architected models and clearly documented transformations

• Experience building structured data layers in Snowflake and dbt (or equivalent), including semantic/metrics definitions that keep reporting consistent across tools

• Experience with marketing measurement concepts (attribution, incrementality, media mix)

• Experience with advanced SQL and Python (or R); production experience with dbt, Airflow, or similar

• Experience with a BI platform (Tableau, Looker, Hex, or equivalent)

Preferred

• Experience in B2B SaaS

• Ability to ship early and iterate working assets over polished decks

• Ability to see fragmented data sources as an opportunity to build something coherent the business relies on

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