Lead Data Scientist, Financial Enablement Analytics

tanding of statistics and ML methodologies, working under the direction of more senior data scientists when asked to take on more complex work.

• Deliver systems that automate, expedite, simulate, predict, validate, audit, diagnose, reconcile, and/or explain.

Data Preparation & Feature Development

• Work closely with Data Engineers to define data requirements, evaluate source data quality, determine needed data transformations, and execute candidate feature engineering.

• Develop and manage ETL pipes in support of specific analytic project work, including understanding and advocating for mixed-use ML/GenAI systems' data requirements.

Deployment, Monitoring & Maintenance

• Work closely with Deployment Engineers to refactor model and feature code for deployment via the Model Ops toolchain, test the model workflow pre-deployment, and deploy and evaluate the model workflow into production.

• Manage maintenance, retraining, or quality control on models actively in production. This includes evaluating the accuracy of predictive ML models and LLM responses-recognizing the non-deterministic nature of GenAI output-and suggesting tuning or feature engineering to address inaccuracies.

• Measure and monitor automated pipeline performance using standard metrics (e.g., accuracy, AUC, bias, calibration, pinball loss, stability, etc.).

Quality, Standards & Tools

• Act as an individual contributor responsible for implementing data science best practices. Own and be accountable for model and code quality and documentation for executed project work.

• Leverage pre-defined cloud compute resources and technology (Databricks, AWS, GitHub)

Collaboration & Stakeholder Management

• Interact with business partners in a hybrid work environment to understand their needs and influence others towards an effective solution.

• Partner closely with Engineering on GenAI component implementation and to utilize data science tools.

• Communicate with, coordinate with, and train users and stakeholders about the advanced analytics products being built and maintained.

Required Qualifications (Knowledge, Skills, & Abilities)

• Has strong analytical and research skills

• Has a strong understanding of statistics and statistical modeling.

• Has a basic understanding of modern ML and its mathematical underpinnings.

• Has moderate programming skills in SQL and [Python and/or R].

• Understanding of deep learning and artificial neural network architecture underlying modern GenAI models

• Familiarity with visualization methods/tools (e.g. Python Matplotlib, R ggplot2, Streamlit, Shiny)

• Has strong written and verbal communication skills.

• Is a quick and versatile learner and a proven problem solver.

• Has a keen eye for system thinking and process design, especially with respect to scalability and automation.

• Has a keen eye for detail and thoughtful investigation of data.

• Has a focus on creating impactful change.

• Has the ability to maintain a focus on the business context and key decisions to be made.

• Has the ability to manage multiple projects and deadlines simultaneously.

• Has experience partnering well with cross-functional teams, being highly collaborative with the ability to build strong relationships.

Preferred Qualifications (Knowledge, Skills, & Abilities)

• Understanding of large language model (LLM) and neural network (NN) architecture.

• Has some experience using the AWS big data technology stack.

• Has any experience developing ML or advanced statistical models.

• Has some professional experience in the restaurant, retail, or hospitality industry.

• Has any experience with Model Operations tools and processes.

• Experience with GenAI coding assistants

Required Years of Experience

3

Preferred Years of Experience

5

Travel Requirements

10%

Required Level of Education

Bachelor's Degree

Preferred Level of Education

Master's Degree

Major/Concentration

Quantitative or technical degree program, including but not limited to: data science, statistics, mathematics, engineering, economics. 3.2 GPA required

Preferred Major/Concentration

MBA or Masters' Degree in a quantitative field, like Business Analytics, Mathematics, Statistics, or other similar fields, and 3.2 GPA

Relocation Assistance Provided

No