Data Scientist - RCM

As a Data Science Analyst, you will play a crucial role in interpreting and analyzing complex data to help inform strategic decision-making across various business functions. You will work with cross-functional teams to gather, process, and analyze data from multiple sources, applying advanced statistical techniques and machine learning algorithms to identify trends, patterns, and actionable insights. The ideal candidate will have strong analytical skills, proficiency in data modeling, and experience in building data-driven solutions.

• Data Analysis: Perform exploratory data analysis (EDA) on structured and unstructured datasets to extract meaningful insights and assist in business decision-making.
• Model Development: Build, test, and deploy machine learning models (supervised and unsupervised) to solve complex business problems, such as predictive analytics, customer segmentation, and anomaly detection.
• Data Wrangling & Preprocessing: Clean, preprocess, and transform raw data into a usable format for analysis using Python, R, and SQL.
• Statistical Analysis: Apply statistical methods to analyze data trends, validate hypotheses, and derive actionable insights from business metrics.
• Reporting & Visualization: Create visualizations and interactive dashboards using tools like Tableau, Power BI, or Python libraries (e.g., Matplotlib, Seaborn) to communicate insights clearly to stakeholders.
• Collaboration: Work closely with business leaders, product teams, and engineering to define data requirements, KPIs, and data strategies.
• Automation & Optimization: Automate repetitive tasks and processes related to data analysis and reporting to enhance productivity.
• Documentation: Maintain detailed documentation of data analysis processes, models, and workflows for future reference and replication.
• Continuous Learning: Stay updated on the latest trends in data science, machine learning, and analytics, and apply new techniques to solve business challenges.

Candidate Requirements

Education:

Bachelor's or Masters degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.

Experience:

Minimum of 3 years of experience in data analysis, statistical modeling, and machine learning.

Technical Skills:

• Proficiency in programming languages such as Python or R.
• Strong knowledge of SQL for data extraction, manipulation, and database management.
• Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn).
• Solid understanding of machine learning algorithms and statistical techniques (e.g., regression, classification, clustering, time-series analysis).
• Familiarity with cloud platforms (e.g., AWS, Google Cloud) is a plus.
• Analytical Skills: Strong analytical thinking with the ability to interpret complex data, identify patterns, and make data-driven recommendations.
• Communication Skills: Excellent written and verbal communication skills with the ability to present complex data insights in an understandable manner to both technical and nontechnical stakeholders.
• Attention to Detail: High attention to detail and ability to maintain data integrity and quality across multiple datasets.
• Collaboration: Ability to work in cross-functional teams and manage multiple projects simultaneously.

Preferred Qualifications

• Experience in handling large-scale datasets and working with big data technologies (e.g., Hadoop, Spark) is a plus.
• Previous experience in US healthcare RCM is preferred.
• Certification in data science, machine learning, or cloud platforms (AWS, Azure) is a plus
• Knowledge of healthcare data standards like HL7, FHIR, and experience with RPA, workflow automation tools.