Senior Data Scientist - Insurance

Posted 8 days agoViewed

💎 Seniority level: Senior, 7+ years

📍 Location: United States

🔍 Industry: Insurance

🏢 Company: Tiger Analytics👥 1001-5000 Advertising Consulting Big Data News Machine Learning Analytics

🗣️ Languages: English

⏳ Experience: 7+ years

Requirements:

Bachelors Degree in Data Science, Computer Science, or related field

7+ years of Data Science and Machine Learning experience required

Experience working on Insurance domain/Insurance / Health Payer (strongly preferred)

Proficiency with Machine Learning concepts and modeling techniques to solve problems such as clustering, classification, regression, anomaly detection, simulation and optimization problems on large scale data sets

Ability to implement ML best practices for the entire Data Science lifecycle

Exceptional communication and collaboration skills to understand business partner needs and deliver solutions

Bias for action, with the ability to deliver outstanding results through task prioritization and time management

Experience with data visualization tools — Tableau, R Shiny, etc. preferred

Responsibilities:

Collaborate with business partners to develop innovative solutions to meet objectives utilizing cutting edge techniques and tools.

Effectively communicate the analytics approach and how it will meet and address objectives to business partners.

Advocate and educate on the value of data-driven decision making; focus on the “how and why” of solutioning.

Lead analytic approaches; integrate solutions collaboratively into applications and tools with data engineers, business leads, analysts and developers.

Create repeatable, interpretable, dynamic and scalable models that are seamlessly incorporated into analytic data products.

Engineer features by using your business acumen to find new ways to combine disparate internal and external data sources.

Share your passion for Data Science with the broader enterprise community; identify and develop long-term processes, frameworks, tools, methods and standards.

Collaborate, coach, and learn with a growing team of experienced Data Scientists.

Stay connected with external sources of ideas through conferences and community engagements.

Apply

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