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Data Scientist (AI, Big Data, SQL, Python) - REMOTE

Resource Point LLCMinneapolis, MN, United States

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Job Title : Data Scientist (AI, Big Data, SQL, Python) - REMOTE

Location : Minneapolis, MN

Duration : 12+ Months

Description :

Our audit and governance functions require a centralized data leader who can :

Architect scalable, secure, compliant data pipelines
Translate complex datasets into actionable insights for regulatory and operational decisions
Build intuitive, low-maintenance tools that empower non-technical users across the PA experience

Responsibilities :

Data Collection & Cleaning - They gather data from various sources and clean it to ensure it's usable-removing errors, filling in missing values, and standardizing formats.

Exploratory Data Analysis (EDA) - They explore the data to understand patterns, trends, and relationships using statistical techniques and visualizations.

Model Building - They build predictive models using machine learning algorithms to forecast outcomes or classify data.

Interpretation & Communication - They translate complex results into actionable insights and communicate them to stakeholders through reports, dashboards, or presentations.

Deployment & Monitoring - In some cases, they help deploy models into production systems and monitor their performance over time.

Ideal Background :

Healthcare specific background would be helpful.

But candidate must be experienced in elements of statistics , computer science, and domain expertise to help organizations make data-driven decisions.

As well as, build and maintain artificial intelligence (AI) driven platforms / solutions.

Required Skills :

Programming : Python, R, SQL

Statistics & Mathematics

Machine Learning & AI

Data Visualization : Tools like Tableau, Power BI, or libraries like Matplotlib and Seaborn

Big Data Tools : Spark, Hadoop (for large-scale data)

Preferred :

Advanced SQL and Python for analytics, ETL, and automation

Data modeling, warehousing, and pipeline orchestration (cloud, native stack)

Dashboarding (Power BI ; Streamlit or similar) and reproducible analytics (versioning, CI / CD preferred)

Healthcare data familiarity (claims, PA & appeals, pharmacy) and regulatory contexts (CMS, NCQA, URAC, ERISA, state rules)

Data security, privacy, and compliance best practices .

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Data Scientist • Minneapolis, MN, United States