., ., United States
17 hours ago
Data Scientist, Healthcare - Remote

Company Description

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realise their financial goals and help them save time and money.

We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments.

We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com

Job Description

Reporting to the Director of Analytics, the Data Scientist drives development efforts on Experian Health priority data science and machine learning projects.

You will:

You are innovative and will help build data science models that addresses critical healthcare challenges for patients.Have a strong background in statistics, analyzing large data sets, building machine learning models, implementing MLOps best practices, and designing experiments with appropriate documentation and cataloging.Have experience as a full-stack data scientist, developing models from project ideation through production.

Qualifications

Qualifications:

Degree(s) in Machine Learning, Data Science, Statistics, Computer Science, Computer Engineering, Electrical Engineering, Physics, Applied Math or other quantitative fields1+ years industry experience in data science and predictive modelingKnowledge of machine learning algorithms, statistical methods, and data mining techniques, with experience applying them to real-world problemsFamiliarity with MLOps practices and tools for model deployment, monitoring, and management in production environments (e.g., Sagemaker, MLflow, or similar ML platform)Experience with model governance including model versioning and experiment trackingStrong proficiency in Python and SQLAs a full-stack data scientist, experience creating data pipelines to source new data for model buildingProven ability to work independently on development of models with extremely large and complex data structures

Desired expertise with:

Strong understanding of healthcare concepts, terminologies, and data (e.g., claims/EHR data, ICD, CPT)Experience with big data technologies such as SparkAgile methods for software development

Benefits/Perks:

You will be fully remote from within the USGreat compensation package and bonus planCore benefits including medical, dental, vision, and matching 401KFlexible work environment, ability to work remote, hybrid or in-officeFlexible time off including volunteer time off, vacation, sick and 12-paid holidays

Additional Information

Our uniqueness is that we celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what matters; DEI, work/life balance, development, authenticity, collaboration, wellness, reward & recognition, volunteering... the list goes on. Experian's people first approach is award-winning; World's Best Workplaces™ 2024 (Fortune Top 25), Great Place To Work™ in 24 countries, and Glassdoor Best Places to Work 2024 to name a few. Check out Experian Life on social or our Careers Site to understand why.

Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is an important part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

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