Data Scientist II - Cole Eye

Cleveland Clinic

2d•Onsite

About The Position

At Cleveland Clinic Health System, we believe in a better future for healthcare. And each of us is responsible for honoring our commitment to excellence, pushing the boundaries and transforming the patient experience, every day. We all have the power to help, heal and change lives — beginning with our own. That’s the power of the Cleveland Clinic Health System team, and The Power of Every One. Join Cleveland Clinic’s Main Campus where research and surgery are advanced, technology is leading-edge, patient care is world-class, and caregivers are family. Cleveland Clinic is recognized as one of the top hospitals in the country. You will work alongside passionate and dedicated caregivers, receive endless support and appreciation, and build a rewarding career with one of the most respected healthcare organizations in the world. Cleveland Clinic’s Cole Eye Institute provides patients with the most advanced level of medical and surgical care, primarily focused on the safe and proven treatment of cases within Ophthalmology. Cole Eye is the first of its kind to unite all specialists in one unique, fully integrated model of care – aimed at optimizing the patient experience. Cleveland Clinic is recognized in the U.S. and throughout the world for its expertise and care. A caregiver in this position works 7:00am to 3:30pm on-site at CC Main Campus.

Requirements

Applicants must reside in Northeast Ohio.
Bachelor’s Degree in Statistician, Actuarial Science, Econometrics, Physics, Biostatistics, Computer Science, Applied Mathematics, Engineering, Business Analytics, Economics, Finance or related field
Excellent written, verbal, and presentation skills in English and ability to explain the value of Machine Learning (ML) and Artificial Intelligence (AI) to business leaders
A minimum of 4 years related experience working with relational databases and/or distributed computing platforms, and their query interfaces, such as SQL, Teradata, MapReduce, PIG, and Hive. Offset: Ph.D. and no relevant experience. Offset: Master’s degree and 2 years of relevant experience.
Experience working with a variety of statistical languages/packages, e.g., SAS, R, Python, Spark, and/or SPSS
Knowledge applying advanced statistics to complex business problems required (e.g., modeling, AI, ML, Deep Learning [DL], and/or Natural Language Processing [NLP])
Familiarity with additional programming languages, including Python, Java, or C/C++
Experience leveraging visualization software and techniques and business intelligence (BI) software
Technical knowledge of distributed computing platforms, and common data process flows from data instrumentation & generation, to ETL, to the data warehouse itself
Demonstrated leadership qualities, including presentation, influencing and negotiation
Ability to perform work in a stationary position for extended periods
Ability to operate a computer and other office equipment
Ability to communicate and exchange accurate information
Ability to travel throughout the hospital system
Follows standard precautions using personal protective equipment as required.

Nice To Haves

Master’s or Ph. D
Certification or fellowship in analytics, big data, data science or related subject
Technology partner certification (in technology, Big data, business or advanced analytics, data science) – Microsoft, Oracle, Teradata, IBM, EMC, Cloudera, Hortonworks, Informatica, Tableau, SAS, R, Python
Healthcare or life science experience
Lead Experience with project management and change management methodologies

Responsibilities

Gather requirements and program model development under direction of other Data Scientists to inform problem formulation.
Participate in model building.
Utilize methods particularly in modeling, Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP) and experience designing/implementing solutions.
Provide insight and recommendations to solve business problems and help inform business decisions.
Document best practices and solution frameworks.
Replicate and scale solutions to business units with common/similar business needs.
Use expertise in defining (with internal clients) the business challenge that needs to be solved, conducting the analysis/modeling/experiment and then providing the “answer” in a clear and business-friendly manner for our clients to take actionable steps.
Participate with more senior data scientists or managers in peer review model assessment and feedback communication.

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