Senior Business Analyst (Data Analytics)

Wolters Kluwer Health's Clinical Effectiveness (CE) organization is a fast-growing and innovation-driven healthcare information technology (HIT) provider working on the front lines of clinical care. Our talented team of physician and pharmacist editors, technologists, and product visionaries collaborate to provide advanced clinical decision support solutions that measurably improve clinical effectiveness by helping healthcare professionals provide optimal care for their patients.  

As our company and client base grows, so do our analysis efforts. This position will help us to refine our current processes and provide enhanced analytics internally and externally.  
 

About You:  
•    You have a deep understanding of data and can translate it into actionable insights. 
•    You love the technical side of data (programming, databases, visualization), but appreciate the business problem at hand and use data to solve those problems.  
•    You can design and implement analytics plans to assess product impact and answer research questions.  
•    You function as a technical expert working alongside analysts, customers, and peers to design, develop, modify, and test data models that meet customer's needs. 
•    You have a thorough understanding of complex large scale data models for healthcare products and business systems and the underlying associated processes. 
•    You adhere to set daily and weekly priorities based on business needs, project impact and management input.  
•    You can address ongoing production and support issues using creativity to resolve issues and ensure the team is proactively supporting custom needs with a stable reporting environment. 
•    You can present analytical findings and business insights to project managers, stakeholders, and senior leadership and keep abreast of new statistical / machine learning techniques and implement them as appropriate to improve predictive performance.
•    You are comfortable in researching and developing production-grade models (forecasting, anomaly detection, optimization, clustering, etc.) for our global business by using statistical and machine learning techniques.

 
Duties and Responsibilities: 
•    Develop a detailed understanding of our products, our customers, and the underlying data.  
•    Build and own end-to-end data solutions utilizing our analytics technologies to answer questions. 
•    Provide meaningful insights to internal and external stakeholders through a combination of descriptive and predictive analytics. 
•    Develop outcomes analyses and case studies to demonstrate impact and prove value in the market. 
•    Perform analytical, technical, and administrative work in the planning, design, testing, and on-going administration of the reporting environments.
•    Ensure efficient functioning of reporting environments, reports, and data driven solutions within all managed environments.
•    Work with Managers and business owners to keep all parties apprised of scope of work and development progress.
•    Proactively review existing code to identify performance enhancing opportunity, data accuracy and efficiency of operations. 
•    Lead innovative ways of presenting complex data concepts and analytics in ways best utilized by the target audience/ business partner. 
•    Facilitate customer relationships and satisfaction while ensuring adherence to company policies and procedures.
•    Coordinate and communicate with team members to effectively leverage resources.
•    Design and maintain documentation and code repositories for all report development and implementation environments. 
•    Work with the Data Architects to develop policies that relate to regulations impacting organizational Data and Business Intelligence Strategy.
•    Work with key stakeholders within other functional areas within the organization to collect and review reporting and analytic requirements.
•    Develop and maintain communications with the customer, management and staff to ensure that service is delivered on time and within contractual obligations.
•    Mentors other team members.
•    Modifies statistical analysis tools for evaluating Machine Learning models. Solves deep and challenging problems for circumstances such as when model predictions are not correct, when models do not match the training data or the design outcomes when the data is not clean when it is unclear which analyses to run, and when the process is ambiguous. 
•    Provides coaching to team members on business context, interpretation, and the implications of findings. Interprets findings and their implications for multiple businesses, and champions methodological rigor by calling attention to the limitations of knowledge wherever biases in data, methods, and analysis exist. 
•    Connects across functional teams and the broader organizat