Job Title: Data Scientist/ Data Engineer
Remote Job
Shift Time :2:00 PM to11:00PAM (Night Shift)
Position Summary:
Leverages statistical modeling and advanced analytics tools to organize large volumes of data, solve complex business problems, improve operational efficiency and create data-driven insights. Works with a variety of data sources and collaborates across functional stakeholders to interpret requirements and generate outputs that are user-friendly and actionable to stakeholders.
1. Works with key stakeholders across functional teams to fully explore and frame a business question including objectives, goals, KPIs, decisions the analysis will support and required timing for deliverables
2. Conducts hands-on analysis of patient, operational and financial data using analytical and statistical tools such as SQL, the MedStar Analytics Platform, Alteryx, and others to uncover insights and provide outputs to leadership in a consumable format.
3. Works with both unstructured and structured data, creating new datasets to be used for model development or other analyses
4. Develops queries from scratch including selecting from existing tables, creates current tables, and removes unwanted data
5. Develops, maintains, and improves models using MedStars tools to enhance business knowledge of services, profitability, cost reduction opportunities, and other trends and insights
6. Develops segmentation analytics such as clusters or decision trees
7. Builds and publishes simple workflows with basic data preparation/transformations
8. Assigns user roles/permissions and monitors data usage/workflow execution
9. Builds and leverages predictive tools to enhance the Fiscal Services teams ability to provide strategic advice
10. Collaborates with the Enterprise Analytics and Decision System Support team to maintain data integrity and identify areas of focus for data standardization and definition improvement
11.
Identifies automation candidates and builds models to support delivery of data in a consistently and timely manner
12. Keeps up to date on new tools, methodologies and analyses in the healthcare industry which can be applied to MedStar to drive innovation and enhancement of capabilities over time
Performs other duties as assigned.
- Complies with all policies and standards.
- Utilize all organizational resources effectively and efficiently.
Where applicable, refer to the competency validation documents for population(s) served.
Education
Education Level -- Required/ Preferred
Required
Bachelor’s degree Computer science, mathematics, or statistics / statistical modeling
Preferred
Master’s degree Computer science, mathematics, or statistics / statistical modeling
Work Experience
Experience
3-4 years with below --Required
Experience with SQL, Alteryx, Tableau, Power BI, PeopleSoft (or comparable ERP), Hyperion (or comparable EPM)
Preferred
Predictive modeling experience, understanding of finance and the healthcare industry
Knowledge, Skills and Abilities
KSAs
Proficiency
Experience with programming languages (e.g., SQL, Python, etc).
Ability to frame business questions and create analytics solution using statistical modeling.
Familiarity with data architecture concepts and data mining techniques.
Ability to design and develop interactive dashboards and reports that effectively communicate data insights.
Ability to manipulate data and create queries to cleanse and integrate various types of structured and unstructured data.
Ability to identify trends, patterns, and anomalies in data and develop solutions to address business challenges applying data structuring best practices
Ability to distill large amounts of data into summarized concepts to be presented to executive leadership.
Understanding of functional finance and operational processes and the ability to communicate technical information to non-technical stakeholders.
Mohd Safiuddin Khan
Lead Recruiter
HITEC City, Hyderabad, Telangana
+91-(phone hidden)
[email protected] connect on LinkedIn insightglobal.com
📌 Data Scientist / Data Engineer (Hyderabad)
🏢 Insight Global
📍 Hyderabad