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).

The Global Data Analytics (GDA) Principal Data Scientist is a highly motivated self-starter who is responsible for designing, building, and promoting models and algorithms that power the next generation of machine learning and data science products for the various organizations at Docusign. You will be solving difficult and non-routine problems by applying analytical methods in novel ways. This includes processing, analyzing and interpreting large and complex data sets, with an emphasis on actionable results. You will also need to collaborate closely with Sales, Customer Success, Engineering and other partners to implement model-based solutions, measure the effectiveness of data products and drive growth and customer success. This role will influence and shape the design, architecture, and roadmap for predictive and prescriptive data products for the GTM teams.

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

Responsibility

• Leverage marketing performance data to uncover opportunities across various channels and develop recommendations that optimize marketing expenditures, campaign strategies, and user acquisition cost
• Construct and deploy marketing attribution models and testing frameworks to accurately assess the performance of various marketing channels and optimize budget distribution
• Lead the creation, application and productization of machine learning models for customer segmentation, churn prediction, customer LTV, MMM and MTA models
• Learn and apply various optimization approaches and causal inference techniques to solve business problems
• Ensure marketing models and frameworks tie in closely with broader financial forecasts, providing vital data for leadership and investor communications
• Collaborate with a cross-functional agile team spanning data science, data engineering, product management, and business experts to build new product features that advance our mission to understand our platform and help us sustainably grow as a business
• Lead Data Science projects end-to-end, ensuring cross team collaboration and partnership with business
• Contribute to designing, building, evaluating, shipping, and refining our data products by hands-on ML development
• Mentor junior members of the team on mathematical modeling and ML best practices
• Develop data preparation processes to consolidate heterogeneous datasets and work around data quality issues
• Communicate and present strategic insights to non-technical audiences
• Work within the Machine Learning platform team to deploy models to production using existing and emerging machine learning methods and technologies
• Work with collaborators to translate product requirements into robust, customer-agnostic machine learning success metrics

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.

Basic

• Bachelor's or Master's degree in Physics, Mathematics, Statistics, Computer Science or related field
• 15+ years hands on experience in building data science applications and machine learning pipelines
• Experience with Python both for research and software development purposes
• Experience with common machine learning, deep learning and statistics frameworks and concepts including Large Language Models
• Experience with large data sets, distributed computing and cloud computing platforms
• Experience with relational databases (e.g., SQL)
• Experience in training and deploying machine learning models in production environments
• Experience using machine learning and deep learning algorithms like CatBoost, XGBoost, LGBM, Feed Forward Networks for classification, regression, clustering problems
• Experience across the SaaS domain as a Data Scientist

Preferred

• Knowledge of Apache Airflow, Spark, Snowflake
• Knowledge of Python, SQL, R, etc.
• Ability to break down technical concepts into simple terms to present to diverse, technical, and non-technical audiences
• Proven track records in taking a ML project from 0 to 1 to 10
• Experience working with technologies like AWS, Git and Terraform
• Effective written and verbal communication skills
• Experience with MapReduce Frameworks like Spark, Hadoop, etc.
• Experience with databases like Snowflake, MySQL, Postgres
• Experience with AWS services like MWAA, Lambda, Athena, S3, Sagemaker Experiments, Model Registry, etc. for model training, model deploying and monitoring

Based on applicable legislation, the below details pay ranges in the following locations:

California: $195,500 - $315,775 base salary

Washington and New York (including NYC metro area): $186,200 - $276,125 base salary

This role is also eligible for bonus, equity and benefits.

Global benefits provide options for the following:

• Paid Time Off: earned time off, as well as paid company holidays based on region
• Paid Parental Leave: take up to six months off with your child after birth, adoption or foster care placement
• Full Health Benefits Plans: options for 100% employer paid and minimum employee contribution health plans from day one of employment
• Retirement Plans: select retirement and pension programs with potential for employer contributions
• Learning and Development: options for coaching, online courses and education reimbursements
• Compassionate Care Leave: paid time off following the loss of a loved one and other life-changing events

Working here

Docusign is committed to building trust and making the world more agreeable for our employees, customers and the communities in which we live and work. You can count on us to listen, be honest, and try our best to do what's right, every day. At Docusign, everything is equal.

We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relationships, and to do the work of their life. Best of all, you will be able to feel deep pride in the work you do, because your contribution helps us make the world better than we found it. And for that, you'll be loved by us, our customers, and the world in which we live.

Accommodation

Docusign is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need such an accommodation, or a religious accommodation, during the application process, please contact us at accommodations@docusign.com.

If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at taops@docusign.com for assistance.

Applicant and Candidate Privacy Notice

This position is not eligible for employment in the following states: Alaska, Hawaii, Maine, Mississippi, North Dakota, South Dakota, Vermont, West Virginia and Wyoming.

It's important to us that we build a talented team that is as diverse as our customers and where all employees feel a deep sense of belonging and thrive. We encourage great talent who bring a range of perspectives to apply for our open positions. Docusign is an Equal Opportunity Employer and makes hiring decisions based on experience, skill, aptitude and a can-do approach. We will not discriminate based on race, ethnicity, color, age, sex, religion, national origin, ancestry, pregnancy, sexual orientation, gender identity, gender expression, genetic information, physical or mental disability, registered domestic partner status, caregiver status, marital status, veteran or military status, or any other legally protected category.

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