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Data Scientist

Tampa, FL, US • Posted 4 hours ago • Updated 4 hours ago

Full Time

No Travel Required

On-site

$130000 - $140000/yr

Fitment

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Job Details

Skills

Python
MLOPS
CPG
Databricks
MLFLOW
Machine Learning

Summary

Job Title: Data Scientist
Location: Austin, TX 78757 (or) Tampa, FL 33602 - Onsite
Full-Time

As Data Scientist, you will spearhead the end-to-end development of sales forecasting and demand sensing models for CPG portfolios on Databricks (Azure). Work closely with commercial, supply chain, and engineering teams to build ML solutions that improve forecast accuracy, reduce inventory waste, and support revenue growth. Bring deep ML expertise, strong Python engineering skills, and a nuanced understanding of CPG market dynamics — and you are comfortable translating complex model outputs into clear business recommendations.

Skills / Experience:

8+ years in data science or Applied ML roles; 3+ years of experience in Databricks in production
5+ years of experience in Python — Pandas, PySpark, scikit-learn, Azure ML or Azure ecosystem and Databricks experience in production
5+ years of experience in Supervised, unsupervised Machine Learning (ML) algorithms, forecasting and inventory optimization
5+ years of experience in deep learning algorithms applying to solve forecasting, regression and classification problems
3+ years of experience in building ML models in CPG, FMCG, or Retail analytics industry
3+ years of experience in MLflow or equivalent experiment tracking tool
Master's or PhD in Statistics, CS, or related field (preferred)

Job / Role Description:

Lead end-to-end sales forecasting model development — from data sourcing and feature engineering through model training, validation, and productionisation on Databricks (Azure)
Design and maintain forecasting pipelines — at SKU, category, and regional hierarchy levels — incorporating POS data, promotional calendars, seasonality indices, and external signals (macroeconomic, weather)
Apply CPG domain knowledge — to model promotional uplift, new product introduction curves, product cannibalization, and retailer sell-in/sell-out dynamics into ML features and targets
Operationalise ML models using MLflow on Databricks — manage the model registry, version control experiments, automate retraining schedules, and configure drift monitoring alerts
Collaborate with commercial and supply chain teams — to translate forecast outputs into inventory recommendations, production planning inputs, and revenue growth strategies
Define and enforce data science best practices — modelling standards, experiment documentation, code review guidelines, and reproducibility requirements across the team
Mentor junior data scientists — conduct code reviews, lead knowledge-sharing sessions, support career development, and build a high-performance data science culture
Communicate model insights and forecast accuracy — to senior stakeholders through dashboards, executive briefings, and written reports — making complex model behaviour accessible to business audiences
Drive continuous model improvement — benchmark new algorithms, evaluate AutoML approaches, and run controlled experiments to improve MAPE, bias, and coverage metrics
Partner with data and platform engineers — to ensure feature pipelines on Azure Data Lake / Delta Lake are reliable, scalable, and aligned with model refresh cadence requirements
Communicate effectively with internal and customer stakeholders; Strong interpersonal skills to build and maintain productive relationships with team members
Problem-Solving and Analytical Thinking; Capability to troubleshoot and resolve issues efficiently
Prior experience in working on Agile/Scrum projects with exposure to tools like Jira/Azure DevOps
Provides regular updates, proactive and due diligent to carry out responsibilities

Expected Outcome / What Success Looks Like

Data Scientist is expected to meet customer expectations within accelerated timelines, enabling us to strengthen our capabilities and drive growth in this area
Statistical Analysis & Experimentation - A/B testing, causal inference, and hypothesis testing to measure the business impact of model improvements and pricing interventions
This role offers the opportunity to lead high-impact data science initiatives that directly shape customer outcomes and gain strong visibility with senior leadership

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 10120137
Position Id: 68952-10367-
Posted 4 hours ago

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