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 CategoryDataJob DetailsAbout SalesforceSalesforce 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 were looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforces 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.<ul><li><div><div><div><div>Role Description: As a Strategic Data Scientist, you will own the end-to-end design, development, and production deployment of advanced AI and data-driven solutions. You’ll build scalable machine-learning models with large, heterogeneous datasets to solve complex business challenges and provide proactive, data-driven guidance to our Customer Success organization.Key Responsibilities:Collaborate with customer success, product, engineering, and sales teams to define KPIs and analytical approaches that answer key business questionsDesign, build, and deploy machine learning and AI models (classification, regression, NLP, recommendation engines, etc.) to identify at-risk customers, predict attrition, and assess impact of product offeringsDevelop customized recommendation engines that suggest next-best actions for customers (collaborative filtering, content-based, hybrid, graph-based techniques, etc.)Drive the end-to-end machine learning lifecycle, from data preprocessing and feature engineering to model training, testing, and automated retraining workflowsArchitect high-performance data pipeline for massive, multi-source datasets (streaming, batch, semi-structured), ensuring optimal storage, fast query performance, and high data integrity in hybrid cloud environmentsMonitor production model performance by tracking key metrics like accuracy, drift, and latency. Leverage A/B testing and establish feedback loops to drive continuous improvement and rapid iterationSupport translation of strategic direction into analytical problems and actionable data science initiatives, ensuring data science alignment with organizational goals and long-term visionPresent clear, actionable insights and technical roadmaps to technical and non-technical stakeholders at all levels  Collaborative Partners:Customer Success Leadership: define priority use cases and success metrics for AI-driven initiativesProduct &amp; Engineering: embed data-science solutions into product features and roadmapsData Platform &amp; MLOps: utilize internal infrastructure for data access, orchestration, and scalable deploymentsBusiness Operations &amp; Finance: validate model assumptions, quantify ROI, and support strategic planning  Role Requirements:Education: Bachelor’s or Master’s in quantitative field such asData Science, Computer Science, Statistics, Mathematics, Engineering, or a related disciplineExperience: 2–5 years of hands-on experience building and deploying machine-learning solutions—especially recommender systems—in a SaaS or customer-facing environmentTechnical Proficiency: Proficient in Python (or R) and ML frameworks (scikit-learn, TensorFlow, PyTorch); expertise with data tools (SQL, Spark, Airflow) and cloud platforms (AWS, GCP, Azure)AI &amp; Next-Gen Models: Demonstrated experience with embedding techniques, transformer-based models, and graph ML for large-scale recommendationsBusiness Acumen: Strong analytical mindset; able to translate model outputs into clear business recommendations and track impact through defined KPIsCommunication &amp; Influence: Excellent at distilling complex technical concepts for non-technical audiences and driving alignment across teamsSelf-Starter: Thrives in ambiguous environments; owns projects end-to-end and iterates based on feedback  Preferred Qualifications:Enterprise-Scale Recommenders: Previous hands-on experience building and scaling recommender systems at major technology platformsTop-Tier Consulting Background: Prior experience at a leading strategy firm with demonstrated ability to translate complex analysis into clear recommendationsLLM Proficiency: Hands-on experience leveraging large language models (e.g., GPT-4) for data augmentation, prompt engineering, or analytics automationAdvanced AI Use Cases: Proven track record of applying cutting-edge techniques—transformer fine-tuning, embedding retrieval, graph neural networks— to build production recommender or decision-support systems</div></div></div></div></li></ul><div><div><div></div></div></div>Unleash Your PotentialWhen 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.AccommodationsIf you require assistance due to a disability applying for open positions please submit a request via this <a href="https://careers.mail.salesforce.com/accommodations-request-form" target="_blank">Accommodations Request Form</a>.Posting StatementSalesforce 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. <a target="_blank" href="https://www.eeoc.gov/know-your-rights-workplace-discrimination-illegal">Know your rights: workplace discrimination is illegal.</a> 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.For New York-based roles, the base salary hiring range for this position is $172,000 to $236,500.<h3></h3><h3></h3><h3></h3><h3></h3><h3></h3><h3></h3><h3></h3><h3></h3>

Salesforce

Strategic Data Science, Manager New York - New York

Salesforce

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