HealthPlanOne's mission is to help people find the right health insurance at the right price, so they live healthier lives. We are committed to making the shopping process simpler. Our mission has never been more important than it is today.
The Senior Data Scientist is responsible for leading advanced analytics projects that will allow us to transform data into actionable insights and solutions. As the Senior Data Scientist, you will own the full life cycle of data modeling projects, creating scalable data science solutions to help drive HPOnes business plans.
- The Senior Data Scientist has direct responsibility for supervising the Data Scientist(s)
- Create advanced data models and high-quality analyses for all aspects of our business to discover insights, provide actionable recommendations, and drive outcomes
- Develop and implement predictive models like decision tree, regression using R or similar
- Define and implement new statistical or other mathematical methodologies for specific models or analyses
- Develop end-customer segmentation schemes by analyzing customer behavior
- Partner with business leaders to articulate business requirements for data analyses
- Manage and optimize the processes for data intake, validation and mining, as well as modeling, visualization and communication deliverables
- Oversee the design and delivery of automated reports and dashboard products to display results to internal teams and key stakeholders
- Communicate results and business impacts to stakeholders
- Provide day to day supervision and oversight to team of data scientists
- Performs other related duties as assigned
- Masters Degree in Computer Science, Statistics, Applied Mathematics, or related field
- 10 years experience with data science and advanced analytics with proven record for delivery of data-driven insights to inform strategic decision making
- 5 years experience with SAS (or similar), ETL, data processing, database programming and data analytics
- 3 years in a leadership role
- Experience in data mining and statistical analysis
- Strong understanding of relational databases and data management as well as experience with data aggregation and normalization
- Understanding of various data structures and common methods in data transformation
- Excellent pattern recognition and predictive modeling skills
- Experience conducting analyses and building predictive models using SAS (or similar)
- Experience with programming languages such as Java / Python (or R)
- Experience conducting regression analyses
- Advanced MS Excel expertise (pivot tables, VLOOKUP, report filters, etc.)
- Excellent communication, collaboration, and delegation skills with demonstrated ability to partner with both technical and non-technical stakeholders
- Coursework in at least one of the following: mathematics, business, analytical marketing, information systems, programming/databases, statistics/statistical modeling, finance, economics, or physics
- Experience with business intelligence and data visualization tools preferred (like Domo or Tableau)
- Prolonged periods of sitting at a desk and working on a computer, typically in an office or cubicle environment (constant noise, fluorescent overhead lighting)
Our centers are consistent with CDC guidelines and align with local government orders pertaining to all Company physical locations in relation to COVID-19.
Equal Employment Opportunity (EEO) is a fundamental principle at HPOne, where employment is based upon personal capabilities and qualifications. HPOne does not discriminate because of actual or perceived sex, sexual orientation or preference, gender identity, gender, transgender, race, color, religion, national origin, creed, citizenship status, ancestry, age, marital status, pregnancy, childbirth or related medical conditions, medical conditions including genetic characteristics, mental or physical disability, military and veteran status, or any other protected characteristic as established by law. HPOne requires the necessary drug testing and background checks as part of our pre-employment practices.
Job Type: Full-time
Work Location: One location