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Data Scientist
- Insight Global (Miramar, FL)
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Job Description
This person will be responsible to build and scale enterprise-grade AI/ML products within our centralized Data Science team. This role focuses on developing intelligent, production-ready solutions that power personalization, forecasting, and automation across our digital platforms. The ideal candidate is a strong problem-solver, able to work independently, and comfortable supporting collaboration across time zones—including occasional calls outside standard working hours.
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [email protected] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.
Skills and Requirements
• 3+ years of experience building and deploying ML models in enterprise environments
• Proficiency in PySpark, Python, and ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
• Experience with SQL, Python, Pyspark
• Experience Azure DevOps, ADLS, and Databricks
• Experience with time-series demand forecasting and margin-aware modeling
Strong coding skills and experience with scalable data workflows and model deployment and experience working with recommendation modeling
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