Staff / Principal Product Data Scientist - Slack

Salesforce is hiring a Staff / Principal Product Data Scientist - Slack in San Francisco, United States. It pays $173k-$314k a year and Level rates it ; you can apply on Salesforce.

Level's read on this job

On Level's scale, this data scientist role is Uses AI ●●○○: an ordinary role that requires AI tools.
The listed pay starts close to the typical data scientist posting on Level.
Tools and skills the posting cites include Slack, Agentforce and AI agents.
Level classifies it as a senior role.
Level lists 1,500+ other open roles at Salesforce.

AI in this role

Build and scale product data ecosystems and agentic data delivery platforms to support data-driven decision making at Slack.

slackagentforce

ai-agentsproduct-analyticsdata-sciencepythonsqlmachine-learning

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.

Job Category

Data

Job Details

About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.

We are hiring Staff & Principal Product Data Scientists to help build a world-class data ecosystem that supports and scales data-driven product decision-making at Slack.

As Staff & Principal Product Data Scientists, you will work closely with cross-functional partners to define the product landscape, derive actionable insights, and directly shape product strategy. You’ll partner with Product, Design, and Engineering (PDE), as well as Go-To-Market (GTM) teams, to contribute directly to product development—shaping what we build, how we measure success, and how we iterate.

You will also play a pivotal role in designing and developing Slack’s agentic data delivery platform. By connecting the dots across our data backend, metrics foundations, and insights analyses, you will help us achieve true data self-serve capabilities within an AI and agentic context.

At Slack, we foster a positive, diverse, and supportive culture. We look for people who are curious, bold, and eager to improve every day. Our team values being smart, humble, hardworking, and above all, collaborative.

What you will be doing:

Establish strong partnerships with product stakeholders to identify opportunities, prioritize roadmaps, and implement execution excellence.
Evangelize evidence-based decision-making by partnering with key leaders and driving the general accessibility of data and insights.
Perform evidence-based evaluations of the most important drivers for increased adoption of Slack product capabilities.
Build key success metric frameworks and self-serve reporting to monitor Slack product health.
Prototype foundational data models and partner with Data Engineering functions to elevate these into canonical sources of truth.
Contribute to the design and implementation of Slack's agentic data delivery platform.
Quantitatively identify potential product opportunities to improve user experiences and unlock business value.
Partner closely with Product Researchers to align roadmaps and collaborate on projects to answer complex questions.

What you should have:

5+ years of experience in product data science in related tech industries.
A consistent record of using data to drive product teams to achieve ambitious goals and influence company-level outcomes.
Advanced proficiency in SQL and at least one programming language for data science, such as Python, R, or Scala. Knowledge of workflow orchestration tools like Apache Airflow is highly desirable.
Strong foundation in statistics, experimentation, causal inference, ML, and analytical problem-solving.
Experience working with large-scale data technologies such as Spark, Presto, Hive, Hadoop, or similar distributed data platforms.
Proven ability to communicate complex analytical findings clearly to executive and cross-functional audiences.
A related degree required. A BS degree in a quantitative field (e.g., Computer Science, Economics, Physics); an advanced degree (MS, PhD) is a strong plus.

Unleash Your Potential

When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world.

Accommodations

If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form.

Please note that Salesforce uses artificial intelligence (AI) tools to help our recruiters assess and evaluate candidates’ resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions. Please see our Candidate Privacy Statement for more information about how we use your personal data and your rights, including with regard to use of AI tools and opt out options.

Posting Statement

Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.

At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions. The typical base salary range for this position is $172,500 - $313,700 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $207,800 - $344,700 annually. The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.

How we rate this

Staff / Principal Product Data Scientist - Slack at Salesforce rates 40 out of 100 for how much of the daily work is AI. That makes it Uses AI (AI Level 2 of 4). The level is about AI in the job, not seniority.

Classification

Uses AI. An ordinary role that requires AI tools.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Staff / Principal Product Data Scientist - Slack is an open job at Salesforce.
Level rates this role AI Level 2 of 4: Uses AI.
The listed salary is $173k-$314k a year.
The role is based in California - San Francisco.
The job was posted on September 17, 2026.
Seniority: senior.
Applications are handled by Salesforce. Apply on Salesforce

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsProduct AnalyticsData SciencePythonSQLMachine learningSlackAgentforce

Also common in data scientist jobs at this level

Machine learning LLM AWS Snowflake Databricks

Pay

This job starts at: $173k
Typical data scientist job: $166k

This posting starts close to the typical data scientist job. See data scientist jobs

Questions you could be asked

How do you decide when an AI agent can act on its own versus asking for approval first?
Tell me about a project where product analytics was part of your work. What did you do?
Tell me about a project where data science was part of your work. What did you do?
Tell me about a project where python was part of your work. What did you do?
Tell me about a project where sql was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: AI agents, Product Analytics, Data Science, Python, and SQL. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Put the AI tool in a bullet point about what you did, not just in a skills list. This role treats it as a required part of the job.

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