招聘
Benefits & Perks
•Parental leave program
•Annual team offsites
•Top Tier compensation with equity
•Learning and development stipend
Required Skills
Python
SQL
TensorFlow
Data Scientist
Location: Mexico City
- Latam
Job Category: Data
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'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.
About the Role
We're looking for an experienced Lead/Staff 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. This Lead/Staff 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. 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.
Responsibilities
- As part of the Customer Targeting team within the Marketing Data Science 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, Ad Tech, paid media, data science, customer data, and analytics communities.
- Assume leadership responsibilities and cover the end-to-end data science solution outside of model development. This includes driving projects to completion with minimal supervision, engaging with stakeholders to quantify impact, and planning roadmaps for future enhancements.
- Work independently to manage stakeholder expectations and explore alternative use cases to get better return on investment from the suite of predictive models.
Required Skills
- 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.
- Strong experience using advanced statistical and machine learning techniques such as clustering, linear and logistic regressions, PCA, gradient boosting machines (GBM), support vector machines (SVM), reinforcement learning (RL), 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.
- 8+ years of proficiency with one or more programming languages such as Python, R, Py Spark, 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.
- Excellent presentation skills; ability to articulate data science solutions to a wide audience to drive model use and implementation adoption.
- 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.
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 require assistance due to a disability applying for open positions please submit a request via this Accommodations Request Form.
Equal Opportunity 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 co
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About Salesforce

Salesforce
PublicA cloud-based software company that provides customer relationship management software and applications.
10,001+
Employees
San Francisco
Headquarters
$243B
Valuation
Reviews
4.0
16 reviews
Work Life Balance
3.0
Compensation
3.5
Culture
2.5
Career
3.0
Management
2.0
35%
Recommend to a Friend
Pros
Competitive compensation packages
Remote work flexibility
Good benefits (headphone/internet reimbursement)
Cons
Ongoing layoffs and job insecurity
Poor refresher/yearly stock grants
Condescending interview processes
Salary Ranges
45 data points
Junior/L3
L3
L5
L6
Junior/L3 · Associate Data Engineer
1 reports
$120,510
total / year
Base
$92,700
Stock
-
Bonus
-
$120,510
$120,510
Interview Experience
5 interviews
Difficulty
3.4
/ 5
Offer Rate
20%
Experience
Positive 20%
Neutral 20%
Negative 60%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Final Interview Panel
6
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Past Experience
News & Buzz
Good pay but culture getting worse day by day
Compensation is decent but culture has shifted to high performance focus with constant reorgs and leadership changes
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NaNw ago
WLB not good & culture is getting changed day by day
Internal political situation deteriorating, frequent layoffs impacting remaining employees workload and wellbeing
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Great work life balance but unclear career growth
WLB is great with flexible hours and remote-friendly policies, but promotion opportunities are very limited
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Salesforce Interview Experience
Two technical rounds with friendly interviewers, tested on C, debugging, storage concepts, and algorithm problems
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·
NaNw ago