Group Company: Maxicare Healthcare Corporation
Designation: Junior Data Scientist - Utilization Management
Office Location: Maxicare Tower (Makati City, Metro Manila)
Position description: The Junior Data Scientist is responsible for performing machine learning tasks and creating data analytics reports relevant to managing medical utilization.
Primary Responsibilities: * Perform defined machine learning tasks, ranging from data preprocessing to modeling and evaluation, to solve predictive and prescriptive business problems surrounding medical utilization.
- Conduct exploratory data analysis (EDA) and translate findings to actionable insights to support various stakeholders (especially within Health Network Management and Maxicare Health Services Inc.).
Additional Responsibilities: * Identify opportunities for analytics processes automation and execute accordingly.
Reporting Team
- Reporting Designation: Not specified
- Reporting Department: Utilization Management Department / Health Network Management Division
Educational Qualifications Preferred
- Category: Quantitative field
- Field specialization: Computer Science, Statistics, Mathematics, Physics, Economics, or Engineering
- Degree: Bachelor’s or Master’s degree
- Academic score: Not specified
- Institution tier: Not specified
Required Certification/s: Not specified
Required Training/s: Not specified
Required Work Experience
- Industry: Healthcare / Health Maintenance Organization (HMO) - Inferred
- Role: Data Science (Data Analyst, Business Analyst, or Software Engineer roles are highly desirable)
- Years of experience: 0-1 years
Key Performance Indicators: Deploy 2-4 ML models in a year with high utilization impact helping Projects team for proactive initiatives
Required Competencies: *
Data Storytelling: Can explain technical findings to non-technical stakeholders (e.g., Marketing or Product managers).
- Problem-Solving: Possesses a "curiosity-first" mindset—the ability to take an ambiguous business question and turn it into a data project.
- Portfolio: Must demonstrate 1-2 end-to-end projects covering EDA, predictive/prescriptive modeling, and tangible business impact.
Required Knowledge: *
Statistics: Understanding of probability distributions, hypothesis testing (p-values, t-tests), and descriptive statistics (mean, variance, correlation).
- Linear Algebra & Calculus: Understanding the "why" behind algorithms, specifically matrix multiplication and gradient descent.
- Machine Learning Fundamentals: Supervised Learning (Linear/Logistic Regression, Decision Trees, Random Forests) and Unsupervised Learning (K-Means Clustering, PCA).
Required Skills: *
Programming: Python (Pandas, NumPy, Scikit-learn, Seaborn, Matplotlib) and SQL (JOINs, subqueries, window functions).
- Data Wrangling: Proficiency in handling missing values, outliers, and inconsistent data formats (JSON, CSV, SQL exports).
- Data Visualization: Proficiency in Tableau or Power BI is a plus.
Required Abilities
- Physical: Not specified
- Other: Not specified
Work Environment Details: Not specified
Specific Requirements
- Travel: Not specified
- Vehicle: Not specified
- Work Permit: Not specified
Other Details
- Pay Rate: Not specified
- Contract Types: Not specified
- Time Constraints: Not specified
- Compliance Related: Not specified
- Union Affiliation: Not specified
