Programmers.io
Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Sr Data Scientist in Greenwood Village, CO, with a 4-day onsite requirement. Key skills include advanced data science, Python, SQL, LLMs, and model deployment. Experience in customer analytics is essential. Pay rate is "unknown."
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
April 18, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Greenwood Village, CO
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🧠 - Skills detailed
#Deployment #Model Deployment #BI (Business Intelligence) #AWS (Amazon Web Services) #PySpark #Databricks #AI (Artificial Intelligence) #Monitoring #Pandas #Looker #Python #Storytelling #Classification #Statistics #Cloud #Time Series #ML (Machine Learning) #Visualization #MLflow #Tableau #NumPy #Microsoft Power BI #Programming #SQL (Structured Query Language) #Regression #A/B Testing #Data Processing #Leadership #Data Science #Spark (Apache Spark) #Clustering
Role description
Sr Data Scientist
Mandatory Skills (Core Requirements)
Greenwood village CO
4 days onsite
1. Advanced Data Science & ML Expertise – Strong hands-on experience with regression, classification, tree-based models, clustering, time series, and recommendation systems.
1. Programming & Data Handling – Proficiency in Python (pandas, NumPy, scikit-learn, PySpark) and advanced SQL for large-scale data processing.
1. LLMs & RAG Experience – Practical experience building LLM-powered solutions, prompt engineering, and retrieval-augmented generation pipelines.
1. Statistics & Experimentation – Deep understanding of hypothesis testing, causal inference, A/B testing, and evaluation metrics (ROC, AUC, precision/recall).
1. End-to-End Model Deployment – Ability to take models from prototype to production, including monitoring, governance, and performance tracking.
Secondary Skills (Nice-to-Have / Enhancing Skills)
1. Data Visualization & Storytelling – Experience with tools like Tableau, Power BI, or Looker and ability to communicate insights to executives.
1. Cloud & MLOps Tools – Familiarity with platforms such as AWS, Databricks, MLflow, feature stores, and model registries.
1. Domain Knowledge (Customer Analytics) – Experience in churn, retention, lead scoring, or customer lifecycle analytics in enterprise environments.
1. Responsible AI & Explainability – Knowledge of SHAP, LIME, bias mitigation, and model governance frameworks.
1. Leadership & Business Acumen – Ability to mentor junior team members and align data science solutions with business KPIs like revenue and customer experience.
Sr Data Scientist
Mandatory Skills (Core Requirements)
Greenwood village CO
4 days onsite
1. Advanced Data Science & ML Expertise – Strong hands-on experience with regression, classification, tree-based models, clustering, time series, and recommendation systems.
1. Programming & Data Handling – Proficiency in Python (pandas, NumPy, scikit-learn, PySpark) and advanced SQL for large-scale data processing.
1. LLMs & RAG Experience – Practical experience building LLM-powered solutions, prompt engineering, and retrieval-augmented generation pipelines.
1. Statistics & Experimentation – Deep understanding of hypothesis testing, causal inference, A/B testing, and evaluation metrics (ROC, AUC, precision/recall).
1. End-to-End Model Deployment – Ability to take models from prototype to production, including monitoring, governance, and performance tracking.
Secondary Skills (Nice-to-Have / Enhancing Skills)
1. Data Visualization & Storytelling – Experience with tools like Tableau, Power BI, or Looker and ability to communicate insights to executives.
1. Cloud & MLOps Tools – Familiarity with platforms such as AWS, Databricks, MLflow, feature stores, and model registries.
1. Domain Knowledge (Customer Analytics) – Experience in churn, retention, lead scoring, or customer lifecycle analytics in enterprise environments.
1. Responsible AI & Explainability – Knowledge of SHAP, LIME, bias mitigation, and model governance frameworks.
1. Leadership & Business Acumen – Ability to mentor junior team members and align data science solutions with business KPIs like revenue and customer experience.
