US-MA, US Commercial Data Scientist SR0029394-MZ
The purpose of this role is to partners with the respective Franchise analytics teams to ensure high quality analytic insights, recommendations, and data usage for the supported therapeutic area. Key responsibilities include: Analytics Execute analytics to support Multi-Channel, Patient, Payer/Provider, Life Cycle, Field Force, and Forecasting Determine the ideal methodology to apply for each analysis or process based on data availability and limitations Develop, validate and deploy predictive and diagnostic solutions using reusable code and computing paradigms Advise and recommend specific analyses required to support Product Launch and Life Cycle Management Derive insights and recommendations from research and analyses that address both stated and unstated business questions Use statistical approaches, such as ANOVA, etc., leveraging statistical analysis toolsets, such as R, SPSS and SAS Design and execute machine learning, NLP, Bayesian inference, and other advanced methodologies, as needed Process and analyze large health-related datasets ranging from small to Big Data and integrate and analyze Structured, Semi-structured, and Unstructured data Use tools for accessing, synthesizing, analyzing and reporting data Data Work with database technologies, SQL, NLP, data engineering, Hadoop Zoo, Kibana, visualization tools, graph analysis Own data environment needs for supported Therapeutic Areas and partner with IT to develop data environment Collaboration Act as SME resource for broader Advanced Analytics community within supported therapeutic areas Foster common data-driven viewpoints between stakeholders with divergent views and objectives Connect technical and data skills to business needs to identify improvements with the project lifecycle Proactively deliver analyses and reports based on timing for key planning processes Project Management Meet Franchise Leadership expectations by delivering work on time and within scope Fulfill assigned role within a project team delivering to expectations Manage conflicting individual priorities and is flexible while adapting to changing Franchise needs Ensure Takeda ethics and compliance are continuously met Responsibilities Job Function and Description 80% Deliver recommendations built on models and analytics 20% Develop data environment Education and Experience Requirements 8-10 years of relevant analytical or healthcare experience: substantive education in relevant tools, techniques, and methodologies will be included. Master s in statistics, mathematics, computer science, applied economics, computational biology, computational informatics, or medical informatics Programming skills: Uses Statistical Modelling: e.g. SPSS, SAS, R Machine Learning Tools: e.g. Spark Visualization: e.g. QlikView/QlikSense, Tableau Data Environment: e.g. Datameer (Hadoop) Experience with large scale database applications (e.g., Oracle, Hadoop, Teradata) Experience detailing Big Data environment requirements Familiar with advanced data science methods, such as Hierarchical Bayesian modeling, Machine Learning (Statistical pattern recognition, semi-supervised learning, active learning, deep learning/neural nets, bagging and boosting etc.); Knowledge Representation and reasoning (relationship representation & extraction, ontology, lexicon and related technologies); Automatic knowledge acquisition from text such as semi/unsupervised ontology induction Demonstrated proficiency with statistical methods, e.g. ANCOVA, two-tailed p-test, descriptive statistics, etc. Items in bold are preferred. Key Skills, Abilities, and Competencies Technical Skills Deep experience working with all relevant data sources available within supported therapeutic areas Highly capable to scope efforts to identify business opportunities based on data available Expert skills in creating appropriate logic that answers stated and unstated business questions In-depth analytical and critical thinking skills to resolve issues efficiently and effectively Expertise in selecting and applying the appropriate methodology based on business need and data Extensive experience using structured statistical modeling tools and additional analytical modules or add-ons Expertise in writing reusable code to customize statistical models Applied knowledge of basic descriptive reporting tools for aggregation Business Acumen Understanding of goals and needs of supported functions Able to identify stakeholder needs through voice of customer and relevant data collection Expert in generating insights and recommendations from research and analyses that address both stated and unstated business questions Interpersonal Skills Experienced in presenting insights and conclusions from complex information in an easy to understand way Able to maintain an impartial point of view Builds marketing and sales leadership s confidence through active listening, asking questions and accurately paraphrasing their needs and expectations Proactively engages with stakeholders to build relationships. Recognizes the need to modify communication styles to fit diverse audiences with various levels of expertise Easily manages small projects and multiple tasks Fulfills assigned role within a project team delivering to expectations Complexity and Problem Solving Technical, data and analysis related decisions are within the incumbent s authority. For business and stakeholder related decision he/she consults with the Advanced Analytics Lead Internal and External Contacts Internal Business Partner Contacts Advanced Analytics Community in Franchises U.S. Commercial Operations functions (Sales Operations, Marketing Operations, Learning and Development) IT, Regulatory, Medical, Compliance External Vendor Contracts Service Providers / Consultants Technology Solution Implementation Vendors Software Vendors
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Shire, a wholly-owned subsidiary of Takeda, is an Equal Opportunity Employer committed to a diverse workforce. Shire, a wholly-owned subsidiary of Takeda, will not discriminate against any worker or job applicant on the basis of race, color, religion, gender, national origin, ancestry, age, sexual orientation, marital or civil partnership status, pregnancy, gender reassignment, non-job related mental or physical disability, genetic information, veteran status, military service, application for military service, or membership in any other category protected under law.
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