Data Scientist - Experian Health (Can be Remote from within the US)

at  EXPERIAN

Full-time
Employee Status: Regular
Role Type: Home
Job Posting - Salary Range: $83,093 - $144,028
Department: Analytics
Flexible Time Off: 15 Days
Schedule: Full Time
Shift: Day Shift

COMPANY DESCRIPTION

At Experian Health, our employees can shape more than products – they shape the future of U.S. healthcare. Experian Health is a pioneer for innovations leading the way in revenue cycle management, identity management, patient engagement, and care management for hospitals, physician groups, labs, pharmacies and other risk-bearing entities. Our success relies on people who are given the freedom to imagine new frontiers in the rapidly changing healthcare space and push the boundaries of innovation. Help us realize our vision of applying data for good and changing the healthcare landscape for the better – for all of us.

Our mission is to use data driven insights to simplify healthcare for all. Simply put, we want to make the healthcare system work better for us as consumers and for those who work in healthcare. Our ONE Experian Health culture is the centerpiece of making this happen. Our aspiration is to bring people together who are driven by purpose and want to make a difference. We strive to have a diverse group of people and minds who are:

• OPEN: Have a growth mindset and collaborate often with others to make things happen
• NIMBLE: Always embracing change and pushing the envelope on innovative ways to solve problems
• EFFECTIVE: Accountable to themselves and to others

JOB DESCRIPTION

Experian Health Data Scientist:

• Analyzing, processing, evaluating and documenting large data sets
• Identify/develop appropriate machine learning/natural language understanding/natural language processing techniques to uncover the value of the data
• Developing visualizations for a wider audience
• Designing data structure and data storage schemes for efficient data manipulation and information retrieval
• Developing tools for data processing and information retrieval
• Developing data driven models to quantify the value of a given data set
• Leading research and development projects on machine learning and data analytics.
• Applying, developing and inventing algorithms to solve challenging business problems
• Validating score performance and conducting ROI and benefit analysis
• Documenting and presenting model process and model performance

QUALIFICATIONS

Knowledge, Experience & Qualifications

• Degree(s) in Machine Learning, Data Science, AI, Computer Science, Computer Engineering, Electrical Engineering, Physics, Statistics, Applied Math or other quantitative fields
• 2-5 years of working experience in data science, data visualization, and/or predictive modeling
• Demonstrated ability to lead and execute projects from start to finish
• Ability to independently support existing products
• Proven track record in modifying and applying advanced algorithms to address practical problems
• Experience in regression analysis, machine learning (SVM, GLM, boosting, random forest, etc.), graph models, and/or, reinforcement learning.
• Experience with open source tools for deep learning and machine learning technology such as Keras, tensorflow, pytorch, scikit-learn, pandas, etc.
• Proven ability to work independently on development of models with extremely large and complex data structures
• Proficient in more than one of Python, R, Java, C++, or C
• Proficient in SQL and ETL
• Robust knowledge and experience with statistical methods

Plusses:

• Experience with Hadoop related technologies such as Map Reduce, Spark, Hive, HBase, etc.
• Experience with visualization tools such as Tableau, Qlik, etc.
• Experience with Natural Language Processing, Natural Language Understanding, and the relevant open-source tools
• Experience with Bayesian statistical inference and related machine learning methods.
• Experience with Agile methods for software development

• OPEN: Have a growth mindset and collaborate often with others to make things happen
• NIMBLE: Always embracing change and pushing the envelope on innovative ways to solve problems
• EFFECTIVE: Accountable to themselves and to other