Senior/Lead/Principal Data Scientist
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Job CategoryData, Software Engineering
We’re Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good – you’ve come to the right place.
Each team is made up of data scientists, engineers, growth analysts, and information management experts who are dedicated to driving product strategy with data-driven insights. Teams with executives, product managers, designers, developers, user researchers, marketers, and sales strategy team members across all Cloud businesses to discover new opportunities for growth and optimization, experiment with data, drive adoption, and deliver useful insights that impact product strategy.
As a Data Scientist, you will be partnering with the Product, Sales, Customer Success, Infrastructure, and Engineering teams embedded in the Cloud businesses, as well as functional leaders who provide data and analytical infrastructure, identify and execute initiatives that benefit the whole Di and multiple Cloud businesses. The successful candidate will need to:
Partner with Senior Leadership (VP+) to understand their business and advise on strategic objectives, product direction, roadmaps, growth goals and retention strategies; as a Senior Analyst/ Data Scientist you will develop and own the relationships with senior stakeholders
Technical Excellence: Own the complete cycle of translating ideas from concept to production-grade data science solutions, ensuring scalability and robustness.
Leadership: Provide leadership and mentorship to the data science team, fostering a culture of excellence, innovation, and collaboration, all aimed at driving tangible business outcomes.
Data Science Modeling: Develop and implement advanced data analysis, predictive and prescriptive modeling techniques to extract insights and support data-driven decision-making across the organization.
Produce insights (e.g. performance drivers, retention analysis, behavioral personas) to accelerate business growth; this requires acquiring and cleaning data from multiple sources, structuring and building data models, analyzing to generate insights, and distributing them
Partner with the data engineering team and product engineering team to instrument, acquire, develop and structure data assets that are critical to measuring the success of our products
Own the delivery by working with data engineers and business intelligence engineers to turn insights into data products (e.g. data pipelines, algorithms, self-service dashboards)
Research, develop and implement automated algorithm deployment pipelines and processes
Evangelize and distribute data products that drive action or product improvement
Contribute to expanding the Salesforce data culture by growing new relationships, hosting learning sessions, integrating or designing new tools, and autonomously improving team processes
5+ years of experience in product analytics or data science. Practical project experience in advanced data analysis, statistical modeling, and machine learning concepts is essential.
Analytical thinker with a passion for using data and scientific methods to solve business problems
Proficient with common analytical programming languages e.g. Python; expert in SQL. Experience with writing production-ready code in Python and automation. Solid understanding of data transformations and analytics functions using tools/languages like Pandas, Sklearn, SQL and Spark. Experience tools like R, git, mlFlow, Airflow, Cron, Docker and Cloud Platforms such as AWS/GCP is a plus.
Technical Expertise: Strong proficiency in core Data Science, Machine Learning and Statistical modeling. In-depth experience in techniques from time-series forecasting and/or causal inference. Experience with Experiment Design, Natural Language Processing, Neural Network architectures, Recommendation Systems, and Large Language Models is highly desirable.
Expert in end to end data development, including data model design, quality review, deployment and maintenance
Experienced in developing and deploying data science models, especially in the Cloud environment
Passionate about automating data that directly solving business problem
Charismatic storyteller ready to lead growth conversations with senior leadership
Lover of building relationships and collaborating in a cross-disciplinary environment.
A related technical degree
Experience working with data technologies that allow effective storage and analysis of large amounts of data (e.g. Spark, Presto, Hive, etc.)
Experience in time series forecasting methods
Benefits & Perks
Check out our benefits site which explains our various benefits, including wellbeing reimbursement, generous parental leave, adoption assistance, fertility benefits, and more.
Check out our Salesforce Engineering Site.
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Salesforce is an Equal Employment Opportunity and Affirmative Action Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status. Salesforce does not accept unsolicited headhunter and agency resumes. Salesforce will not pay any third-party agency or company that does not have a signed agreement with Salesforce.
Salesforce welcomes all.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.For Washington-based roles, the base salary hiring range for this position is $172,500 to $237,200.For California-based roles, the base salary hiring range for this position is $188,200 to $258,700.Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, benefits. More details about our company benefits can be found at the following link: https://www.salesforcebenefits.com.