QBA Worldwide
Sr. Data Scientist (Databricks, PySpark, SQL)
QBA Worldwide, Minneapolis, Minnesota, United States, 55400
Sr. Data Scientist (Databricks, PySpark, SQL)
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Sr. Data Scientist (Databricks, PySpark, SQL)
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QBA Worldwide Job Title:
Sr. Data Scientist (Databricks, PySpark, SQL) Location: Remote (100%) Base Location: Minneapolis, MN Duration:
Start Date: 09/29/2025 End Date: 06/30/2026 Position Type: Contract to Perm Position Background & Impact The Sr. Data Scientist will play a critical role in building scalable data pipelines and ML models to drive insights, enhance operational efficiency, and support data-driven business decisions. They will work across teams to identify business challenges, improve data quality, and create solutions leveraging Databricks, PySpark, and ML frameworks. Responsibilities:
Develop & deploy scalable data pipelines using Databricks and PySpark. Design & implement machine learning models in Python (Scikit-learn, TensorFlow, PyTorch). Work with cross-functional teams to translate business problems into data-driven solutions. Perform data cleansing, feature engineering, and ensure consistency. Create & maintain technical documentation for ML models and pipelines. Collaborate with stakeholders to identify, prioritize, and execute projects. Build data visualizations (Tableau, Power BI, Python) to present insights. Stay updated on emerging trends in Data Science, AI/ML, and big data. Partner with data engineers for data quality, governance, and optimization. Contribute to code reviews, best practices, and knowledge sharing. Required Skills:
3+ years Databricks & PySpark. 2+ years Python (Scikit-learn, TensorFlow, PyTorch). 2+ years SQL & Data Warehousing. Hands-on with data cleansing, feature engineering. ML model development & deployment experience. Strong problem-solving and communication skills. Highly Desired Skills (Nice-to-Have):
Healthcare industry knowledge. Experience with data visualization tools (Tableau, Power BI). Exposure to R or additional ML frameworks. Knowledge of cloud-based data engineering practices. Mandatory Skills (Must-Have):
Databricks → 3+ years hands-on experience PySpark → 3+ years building scalable pipelines SQL & Data Warehousing → 2+ years Python (Data Science libraries) → 2+ years with Scikit-learn, TensorFlow, or PyTorch Machine Learning model development & deployment experience Data cleansing & feature engineering techniques expertise Strong communication & collaboration skills.
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Join us to apply for the
Sr. Data Scientist (Databricks, PySpark, SQL)
role at
QBA Worldwide Job Title:
Sr. Data Scientist (Databricks, PySpark, SQL) Location: Remote (100%) Base Location: Minneapolis, MN Duration:
Start Date: 09/29/2025 End Date: 06/30/2026 Position Type: Contract to Perm Position Background & Impact The Sr. Data Scientist will play a critical role in building scalable data pipelines and ML models to drive insights, enhance operational efficiency, and support data-driven business decisions. They will work across teams to identify business challenges, improve data quality, and create solutions leveraging Databricks, PySpark, and ML frameworks. Responsibilities:
Develop & deploy scalable data pipelines using Databricks and PySpark. Design & implement machine learning models in Python (Scikit-learn, TensorFlow, PyTorch). Work with cross-functional teams to translate business problems into data-driven solutions. Perform data cleansing, feature engineering, and ensure consistency. Create & maintain technical documentation for ML models and pipelines. Collaborate with stakeholders to identify, prioritize, and execute projects. Build data visualizations (Tableau, Power BI, Python) to present insights. Stay updated on emerging trends in Data Science, AI/ML, and big data. Partner with data engineers for data quality, governance, and optimization. Contribute to code reviews, best practices, and knowledge sharing. Required Skills:
3+ years Databricks & PySpark. 2+ years Python (Scikit-learn, TensorFlow, PyTorch). 2+ years SQL & Data Warehousing. Hands-on with data cleansing, feature engineering. ML model development & deployment experience. Strong problem-solving and communication skills. Highly Desired Skills (Nice-to-Have):
Healthcare industry knowledge. Experience with data visualization tools (Tableau, Power BI). Exposure to R or additional ML frameworks. Knowledge of cloud-based data engineering practices. Mandatory Skills (Must-Have):
Databricks → 3+ years hands-on experience PySpark → 3+ years building scalable pipelines SQL & Data Warehousing → 2+ years Python (Data Science libraries) → 2+ years with Scikit-learn, TensorFlow, or PyTorch Machine Learning model development & deployment experience Data cleansing & feature engineering techniques expertise Strong communication & collaboration skills.
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