Senior Data Scientist, Salesforce
Marketing Customer Modeling
$165.6-227.7k
Salary applicable to candidates based in CA
World's leading CRM provider
Job no longer available
World's leading CRM provider
1001+ employees
Job no longer available
$165.6-227.7k
Salary applicable to candidates based in CA
1001+ employees
Company mission
To empower companies to connect with their customers in a whole new way.
Role
Who you are
- This Data Scientist brings significant experience in designing, developing, and delivering statistical models and machine learning algorithms for targeting and digital optimization use cases on large-scale data sets in a cloud environment.
- They show rigor in how they prototype, test, and evaluate algorithm performance both in the testing phase of algorithm development and in managing production algorithms
- They demonstrate advanced knowledge of machine learning and statistical techniques along with ensuring the ethical use of data in the algorithm design process
- Master’s or Ph.D. in a quantitative field such as statistics, economics, computer science, industrial engineering and operations research, applied math, or other relevant quantitative field
- 5+ years of experience using advanced statistical and machine learning techniques such as clustering, linear and logistic regressions, PCA, gradient boosting machines (GBM), support vector machines (SVM), neural networks (e.g., ANN, RNN, CNN), and other deep learning algorithms (e.g., Wide & Deep). Must have multiple robust examples of using these techniques to support marketing efforts and to solve business problems on large-scale data sets
- 5+ years of proficiency with one or more programming languages such as Python, R, PySpark, Java
- Expert-level knowledge of SQL with strong data exploration and manipulation skills
- Experience using cloud platforms such as GCP and AWS for model development and operationalization is preferred
- Experience developing production-ready feature engineering scripts for model scoring deployment
- Experience transforming semi-structured and unstructured data into features for model development
- Experience creating model monitoring and model re-training frameworks to validate and optimize in-production performance
- Must have superb quantitative reasoning and interpretation skills with strong ability to provide analysis-driven business insight and recommendations
- Excellent written and verbal communication skills; ability to work well with peers and leaders across data science, marketing, and engineering organizations
- Creative problem-solver who simplifies problems to their core elements
- Experience with setting up endpoints, lambda functions, and API gateways is a plus
- B2B customer data experience a big plus. Advanced Salesforce product knowledge is also a plus
What the job involves
- We’re looking for an experienced Data Scientist who will help us build predictive models and recommender systems using machine learning and statistical techniques to drive personalized marketing and customer experience.
- At Salesforce, Trust is our number one value and we expect all applications of statistical and machine learning models to adhere to our values and policies to ensure we balance business needs with responsible uses of technology
- As part of the Customer Modeling Data Science team within the Marketing AI/ML Algorithms & Applications organization, develop machine learning algorithms and statistical models to drive effective marketing and personalized customer experience - e.g., propensity models, uplift models, next-best recommender systems, customer lifetime value, etc
- Own the full lifecycle of model development from ideation and data exploration, algorithm design, validation, and testing. Work closely with data engineers to develop modeling data sets and pipelines; deploy models in production, setup model monitoring and in-production tuning processes
- Be a master in cross-functional collaboration by developing deep relationships with key partners across the company and coordinating with working teams
- Collaborate with stakeholders to translate business requirements into technical specifications, and present data science solutions to technical and non-technical audiences technical and non-technical across the organization
- Constantly learn, have a clear pulse on innovation across the enterprise SaaS, AdTech, paid media, data science, customer data, and analytics communities
Our take
Salesforce is a global cloud computing company, best known for its on-demand, comprehensive customer relationship management (CRM) solutions. The company was launched to mitigate the doubts that business owners felt regarding third party companies holding their data.
By providing essential, customer-oriented CRM software, Salesforce places itself at the heart of digitised businesses. Furthermore, by building out its AI capabilities, the company removes the complexity of AI, enabling any business to deliver smarter, personalised and more predictive customer experiences.
Due to the continued innovation offered by the company, over 150,000 companies, both big and small, are growing their business with Salesforce today. Despite a tumultuous 2023 filled with activist investors, a boardroom shake-up and the unprecedented step-down of Co-CEO Bret Taylor, Salesforce continues to close several acquisition deals and managed to drive up its stock value by 96% from the end of 2022 to 2023.
Steph
Company Specialist at Welcome to the Jungle
Insights
-8% employee growth in 12 months
Company
Funding (last 2 of 4 rounds)
Jun 2001
$46.9m
SERIES D
Nov 1999
$13.2m
SERIES C
Total funding: $64.5m
Company benefits
- With 9 standard holidays and four floating holidays, you get a total 13 paid days off each year
Company HQ
SoMa, San Francisco, CA
Leadership
Marc Benioff
(Chair & CEO)Previously Senior Vice President at Oracle Corporation for 13 years.
Parker Harris
(CTO)Previously worked as a Software Engineer for over six years. Harris also co-founded Left Coast Software.
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