Lead/Staff Data Scientist

Job description

Overview

LEAD / STAFF DATA SCIENCE

Mexico City - Latam

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.

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 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.
  
  
• 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.
  
  
• 8+ 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), 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, 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.
  
  
• 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.
  
  

Required Skill Profession

Biología, Biotecnología Y Química