Job Description

Description:
Specific Title of the Position: Data Scientist - Databricks/PySpark
Work Location: Remote/Telecommute
Work Hours: Estimated 8 hours/day, with flexible hours to accommodate remote work arrangements (e.g., 9am-5pm EST, but not strictly enforced).

Position Background and Business Impact:

The Data Scientist - Databricks/PySpark will play a critical role in driving business growth and improving operational efficiency by developing and deploying data-driven solutions using Databricks, PySpark, and other related technologies. This position will accomplish the following for the business:

• Develop and deploy scalable data pipelines and machine learning models to drive business insights and decision-making.
• Improve data quality and consistency through data cleansing and feature engineering techniques.
• Collaborate with cross-functional teams to identify business problems and develop data-driven solutions.

• Team Description: The Data Scientist - Databricks/PySpark will be working with a team of 8-10 data scientists and engineers with diverse skill sets, including:
• Data engineering (Databricks, PySpark, SQL)
• Machine learning (Python, R, TensorFlow, PyTorch)
• Data analysis and visualization (Tableau, Power BI)
• Business acumen (healthcare industry knowledge, business operations)
• The team culture is collaborative, dynamic, and focused on delivering high-quality results.

Top 5-10 Responsibilities:

• Develop and deploy scalable data pipelines using Databricks and PySpark.
• Design and implement machine learning models using Python and related libraries (e.g., Scikit-learn, TensorFlow).
• Collaborate with cross-functional teams to identify business problems and develop data-driven solutions.
• Perform data cleansing and feature engineering to improve data quality and consistency.
• Develop and maintain technical documentation for data pipelines and machine learning models.
• Work with stakeholders to identify and prioritize data-driven projects.
• Develop and deploy data visualizations to communicate insights to business stakeholders.
• Stay up-to-date with emerging trends and technologies in data science and machine learning.
• Collaborate with data engineers to ensure data quality and consistency.
• Participate in code reviews and contribute to the development of best practices for data science and engineering.

Ideal Candidate Background:

• 5+ years of experience in data science or a related field.
• Healthcare industry experience is a plus, but not required.
• Strong background in data engineering (Databricks, PySpark, SQL).
• Experience with machine learning (Python, R, TensorFlow, PyTorch).
• Required Skills/Attributes:
• 3+ years of experience with Databricks and PySpark.
• 2+ years of experience with Python and related libraries (e.g., Scikit-learn, TensorFlow).
• 2+ years of experience with SQL and data warehousing.
• Strong understanding of data cleansing and feature engineering techniques.
• Experience with machine learning model development and deployment.
• Excellent communication and collaboration skills.

Preferred Skills/Attributes:

• Experience with cloud-based data platforms (Azure).
• Experience with Agile development methodologies.
• Certification in data science or a related field (e.g., Certified Data Scientist).
• Professional License or Certification: Not required, but certifications like Certified Data Scientist or Certified Analytics Professional are a plus.

Required Skills : Data Analysis

Basic Qualification :

Additional Skills :

This is a high PRIORITY requisition. This is a PROACTIVE requisition

Background Check : No

Drug Screen : No

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