Project Manager/Analyst Resume

SUMMARY:

In a telecommunication call center project in Beijing, Confidential , co - directed the effort to build-out and launch a customer service call center matching an in-house designed and built customer relationship management (CRM) software application with a Nortel switch. With 2 ex-pat exceptions, all managers and customer service reps were locally recruited from Beijing universities and trained in-house on the concept of “customer service”, a concept that, at the time, did not exist in the Mandarin lexicon. The call center went live on schedule and went cash positive 9 months ahead of schedule.
As an avid sailor and crewmember, have made two Atlantic crossings, and one Boston to Guayaquil, Ecuador trip that included a transit of the Panama Canal. Acquired and have maintained licensing as Confidential Captain (Master 50 Ton) with sail endorsement. Active ASA sailing instructor and charter captain.
Achieved numerous project management successes based on the implementation and progressive use of agile principles and positive psychology in the development and management of project teams, as well as communicating with and advising project stakeholders.
In a naval expansion project, successfully influenced the planning, preventative and corrective maintenance activities of 105+ system technicians and training engineers, resulting in the redesign of existing maintenance protocols/practices that reduced annual project costs by 11%, achieved a weapons system uptime of 94% (from 72%), and reduced ex-pat turnover by 32%.
From a predictive genetics perspective, made creative use of appropriate data science strategies to access and greatly expand the use of clinical data housed in the organization’s electronic health record. As a result, this new data set was used to make demonstrable improvements in the identification and selection of the most harmful cancers and their impact on patient morbidity, thereby enabling the physician group to schedule intensive screening and treatment options for those patients considered to be at significantly greater risk for those cancers.
Serving as a change agent, have made very good use of Lean Six Sigma tools in a variety of operational environments to assess and, where appropriate, enhance existing and/or in corporate new processes, reduce cycle time, eliminate defects and increase efficiencies. Such activities have ranged from those as simple as Just-Do-It strategies to complex A3 problem resolution.

EXPERTISE AREA:

Networks & Graphical Models
Predictive modeling
Hypothesis testing and anomaly detection
Predictive genetics
Regression & Prediction
Business analysis
Jupyter
Python programming
R programming
Agile project management including: backlog analysis sprint planning daily scrums sprint review meetings sprint retrospective meetings
Agile sprints
Value stream mapping
Enterprise requirements modeling & solution delivery
Epic electronic health record (EHR)
Process optimization for Epic EHR ambulatory and health information management (HIM)
Positive psychology for team development and optimization
Spanish and Russian foreign languages

PROFESSIONAL HISTORY:

Project Manager/Analyst

Confidential

Responsibilities:

Data science activities focus on data engineering and business development, such as ROI optimization, decision sciences, and tasks related to business analysis including dashboard design, metric mix selection and metric definitions, ROI optimization, high-level database design, and others.
Utilize big data science methodologies in the development and implementation of gene therapy patient tracking systems used to advise Chief Medical Officers (CMO) and other C-suite decision making - hard data that helps management avoid many of the risks associated with the improper use of big data analytics
Optimize organizational business analysis activities through the automation of production reports and data extraction, often resulting in 100x bigger data pods and at speeds 10x faster than what existed prior to the upgrades
Utilize machine learning algorithms for data mining, then follow up with methodologies for Regression and Prediction
Interpret analytical models through classification, hypothesis testing and anomaly detection, and then apply the results to effect improved C-level decision making
Introduce and manage the proper scaling of big data algorithms intended to produce optimal recommendations supported by network and graphic models

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