Data Scientist

Cavallo•Grand Rapids, MI

About The Position

At Cavallo, we know the importance of being data-driven. Using our customers' data and advanced data science, we are building products that allow our customers to flourish and thrive. Data is a pillar of our core values; it fuels more informed and efficient decision-making and empowers us to build the tools that help our customers to run a more profitable business. We are seeking a Data Scientist to join our Product Development Data Science Team. In this role, you will be an integral part of the engineering cycle, building scalable predictive and statistical models that are embedded directly into our software.

Requirements

2-4+ years of experience in data science, ideally within a software development or SaaS environment.
Bachelor’s degree in a quantitative field.
Advanced knowledge of Python and a strong foundation in mathematics, statistical analysis, and data mining.
Proficiency in SQL with proven experience extracting and transforming data directly from production databases. You are comfortable navigating complex schemas to prepare and structure data for advanced modeling.
Possess deep expertise in modern AI/Machine Learning concepts and pattern recognition. Demonstrate mastery of Pandas and Scikit-learn, paired with a comprehensive grasp of algorithms such as LightGBM or XGBoost and other predictive modeling techniques.
Proficiency with Git for version control and experience working within an Agile/Scrum framework. You are comfortable using tools like Jira to manage tasks within a product development sprint cycle.

Nice To Haves

Familiarity with LLMs and RAG techniques to build natural-language interfaces for complex data insights.
A natural curiosity for "connecting the dots" and a passion for creative problem-solving.
A strong sense of personal ownership, accountability, and attention to detail.
Self-motivated and eager to learn, share knowledge, and grow within a collaborative team.

Responsibilities

Own the full data science lifecycle—from navigating production databases and transforming raw signals into robust features, to collaborating on the deployment of machine learning models that power intelligent product features.
Partner with Product Teams to translate business goals into data-driven strategies that enhance product value.
Analyze complex business problems in the distribution space and use mathematical frameworks/ AI/ ML to deliver models that identify margin opportunities and drive customer profitability.
Bridge the gap between complex model outputs and daily business operations by ensuring data findings are integrated, actionable, and "human-readable" for our customers.
Translate complex statistical findings into clear, visual narratives and actionable insights that enable stakeholders to make confident, data-backed decisions.