Data Sr Scientist (609179) - Business Intelligence/ Data Mining

Zimmer Biomet Connected Health is building digital health tools to improve the care experience for patients, surgeons, and clinicians in musculoskeletal health. Our mission is to deliver digital tools that provide data-driven insights into movement health, support patients through the surgical journey, and empower surgeons with clinical decision support. Our team integrates health data, software, smart devices, and people into a platform for value-based healthcare. This is your chance to join a small but very talented team and have a meaningful impact on people's movement health. We have a startup culture and deliver impact on large company scale.
The role of the Data Scientist is to help establish a data science program to assist in the analysis of clinical data we are collecting through our commercial e-health platform. The primary focus will be in applying data mining techniques, performing statistical analysis, and building high quality predictive systems that will augment our software solutions and assist our customers and patients in making better informed health care decisions.
Principal Duties and Responsibilities
Research and develop statistical learning models for data analysis
Collaborate with product and development teams devise new statistical and other mathematical models for analysis of data
Assist in selecting features and building/ optimizing classifiers by using machine learning techniques
Use state-of-the-art tools and methodologies to perform data mining
Integrate with third party data sources to expand and extend analysis
Develop techniques for verifying the integrity of collected data and identify opportunities for the creation of automated anomaly detection systems
Work with delivery team to perform ad-hoc analyses and presentation of findings
Provide statistical analysis to support clinical studies and investigators with white papers and publications
Expected Areas of Competence
Excellent understanding of foundational statistical methods such as exploratory data analysis, data visualization, and hypothesis testing
Excellent understanding of machine learning techniques and algorithms, such as linear and logistic regression, k-NN, Naive Bayes, SVM, Decision Forests, time series analysis, neural networks, etc.
Experience with data science toolkits, including Python, SAS, R, Weka, NumPy, MatLab, etc. Excellence in at least one of these is required, and competence in more than one is highly desirable
Experience with data visualization tools, such as D3.js, GGplot, etc.
Proficiency in using query languages such as SQL, Hive, Pig, MDX, LINQ and/or DMX
Practical knowledge with NoSQL databases such as MongoDB, Cassandra or HBase
Proven applied statistics skills, such as distribution, statistical testing, regression, and experience with a statistics platform such as SPSS or SAS
Data-oriented personality and great communication skills
Education/Experience Requirements
Minimum requirement of Bachelor's degree in Computer Science, Math or Statistics with a concentration in analytics, business intelligence and/or data mining.
Preferred requirement of Master's degree in Computer Science, Math or Statistics with a concentration in analytics, business intelligence and/or data mining.
5+ years of experience in computational statistics and data analysis
Travel Requirements
Up to 10%
Additional Information

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