Data Science Analyst

Gravity IT Resources; Miami (FL); Hybrid; USD 90,000 - 130,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Gravity IT Resources is seeking a Data Science Analyst in Miami with a focus on casino technology analytics. You will build ML and statistical models, perform EDA on large datasets, and develop segmentation and marketing analytics to guide decisions.

You will collaborate across Marketing, Operations, Finance, Technology, and Data Engineering, turning insights into actionable recommendations for leadership while ensuring data quality and governance.

Qualifications

• 2+ years of experience in data science, advanced analytics, or a similar analytical role.
• Proficient in Python and SQL with Databricks experience.
• Experience building and validating predictive models (regression, classification, time-series).
• Experience with dashboards/reports in Power BI or Tableau.
• Experience with experimental design and A/B testing.
• Excellent written and verbal communication; able to explain analysis to non-technical stakeholders.

Responsibilities

• Build and maintain machine learning and statistical models for casino marketing/ops.
• Perform exploratory data analysis on large casino/loyalty datasets.
• Develop guest segmentation and demographic analyses for pricing/marketing.
• Design experiments and holdouts to measure business impact.
• Write Python/SQL in Databricks notebooks, scripts, and pipelines.
• Convert Alteryx workflows to Python notebooks and Databricks pipelines.
• Build dashboards and recurring reports for stakeholders.
• Monitor data quality with Data Engineering and resolve issues.
• Translate model outputs into clear recommendations for leadership.

Skills

Python (pandas, NumPy, PySpark)

Advanced SQL

AI-assisted tools (Claude Code, GitHub

Data visualization (Power BI, Tableau)

Modeling (regression, classification,

Experimental design (A/B testing)

Communication skills

Education

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or related field

Tools

Databricks

Alteryx

Power BI

Tableau

Unity Catalog

Kafka

MLflow

GitHub

Jira

Confluence

Azure/AWS

Job description

Location: Miami, FL (Hybrid: onsite 2–3 days per week; onsite availability strongly preferred)

Overview

Our client is seeking a Data Science Analyst to join its Casino Technology and Analytics team. The role applies advanced analytics and machine learning to casino, loyalty, and guest data, building forecasting, segmentation, and measurement models that support casino marketing and operations decisions. Working alongside the team's data scientists, this person will partner with Casino Marketing, Casino Operations, Finance, Technology, and Data Engineering. They will turn complex analysis into clear recommendations for business stakeholders and leadership.

• Key Responsibilities Build and maintain machine learning and statistical models that support casino marketing and operations decisions
• Run ad hoc exploratory data analysis (EDA) on large casino, loyalty, and guest datasets to find revenue and efficiency opportunities
• Develop guest segmentation and demographic analysis to support personalized marketing and pricing models
• Design and analyze experiments and holdout tests to measure the business impact of analytical work
• Write Python and SQL in Databricks notebooks, scripts, and pipelines
• Convert existing Alteryx workflows into maintainable Python notebooks, scripts, and Databricks pipelines
• Build dashboards and recurring reports that give Casino Marketing, Operations, and Finance clear visibility into performance
• Monitor data quality and work with Data Engineering to resolve gaps, latency, or schema issues
• Use AI-assisted development tools (Claude Code, GitHub Copilot) to speed up model development, testing, documentation, and code review
• Translate model outputs into plain recommendations for non-technical stakeholders and present findings to leadership
• Document data definitions, model assumptions, and methodology so work is repeatable across teams and brands
• Follow company data-handling, privacy, and security standards when working with guest and loyalty data
• Key Requirements2+ years of experience in data science, advanced analytics, or a similar analytical role
• Strong Python (pandas, NumPy, PySpark) and advanced SQL skills
• Hands-on Databricks experience, including notebooks, jobs, pipelines, and Unity Catalog
• Hands-on experience building and validating predictive models such as regression, classification, time-series forecasting, or clustering
• Working knowledge of experimental design, including A/B testing, holdouts, and causal measurement of lift
• Daily, current use of AI-assisted development tools (Claude Code, GitHub Copilot), with the judgment to validate AI output
• Experience building dashboards or reports in Power BI or Tableau
• Excellent written and verbal communication skills, with the ability to explain complex analysis clearly to business and executive audiences
• Strong visual storytelling: able to present workflows, model logic, and findings in diagrams non-technical stakeholders can follow
• Must be authorized to work in the U.S. without sponsorship
• Education Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related field, or equivalent experience
• Desired, But Not Required Knowledge Casino gaming industry experience as an analyst, mathematician, or game designer (highly preferred), including understanding of return-to-player (RTP), theoretical win, and how rewards are distributed across player sessions
• Familiarity with player tracking, slot telemetry, comp and offer optimization, or reinvestment modeling
• Experience in hospitality, cruise, travel, retail, or loyalty analytics
• Working knowledge of Alteryx
• Experience deploying models into production, including monitoring, retraining, and MLflow
• Experience with streaming or near real-time data (e.g., Kafka) and cloud platforms (Azure or AWS)
• Familiarity with CRM, loyalty, or offer‑management platforms, plus GitHub, Jira, and Confluence