01Responsibilities
Data Integration & Management
Explore and analyze common pharmaceuticals data (e.g., claims) as well as novel data sets based on lab and EHR systems. Work with Omnichannel Data Engineer to Integrate data from multiple sources (e.g., CRM systems, social media, email platforms) to create a unified view of stakeholder interactions.
Apply natural language processing (NLP) to extract insights from unstructured medical texts, such as clinical notes or call center transcripts.
Identifying relevant data drivers (features) that can inform decision making closely tied with strategy and creating visualizations to help communicate findings.
Advanced Analytics & Modeling
Implement advanced analytics models, including predictive analytics and clustering algorithms, to generate actionable insights and track trends across various channels.
Work with Omnichannel ML/Ops engineer to build, test, and deploy production-grade predictive models and algorithms as part of the Omnichannel COE decision engine to meet business needs, including optimization of sales activities and predicting drivers of customer behavior.
Create repeatable, interpretable, dynamic, and scalable models that are seamlessly incorporated into analytic data products and match the needs of Otsuka's growing portfolio.
Collaborate on MLOPS life cycle experience with MLOPS workflows traceability and versioning of datasets. Build and maintain familiarity with Otsuka Machine Learning tech stack including AWS, Kubernetes, Snowflake, and Dataiku
Omnichannel Optimization
Design and deploy recommendation systems to tailor communications based on stakeholder preferences and behaviors. Utilize machine learning algorithms (e.g., collaborative filtering, content-based filtering) to enhance personalization efforts.
Analyze the performance of omnichannel campaigns (email, SMS, in-app, HCP portals, etc.) to identify high-impact touchpoints and optimize engagement strategies. Use A/B testing and uplift modeling to evaluate the effectiveness of different communication strategies and content types.
Stakeholder Collaboration
Effectively communicating analytical approach to address strategic objectives to business partners.
Work closely with medical affairs, marketing, and IT teams to ensure alignment and integration of omnichannel strategies. Provide technical guidance and support to cross-functional teams on data-related projects.
Stay updated with emerging industrial trends (Conferences and community engagement) and develop strategic industry partnerships on Omnichannel analytics to strengthen Otsuka's analytical methods and outcomes.
Model Otsuka's core competencies (Accountability for Results, Strategic Thinking & Problem Solving, Patient & Customer Centricity, Impact Communications, Respectful Collaboration & Empowered Development) that define how we work together at Otsuka. Key matrixed partners included: Brand Marketing, Creative / CRM / Digital agencies, Media, Market Research, Analytics, Otsuka Information Technology (OIT), Sales Operations, and Medical/Regulatory/Legal integrated business partners.
Minimum Qualification:
Bachelor's degree in data sciences, computer science and 4-6 years of relevant experience
Preferred Knowledge, Skills, and Abilities:
Demonstrated experience with scripting and implementing data analytics algorithms and models. Hands on experience using a modeling and simulation software (e.g. Python, Matlab, R, NONMEM, SAS, S-Plus, etc.) is a plus.
Knowledge/Experience in the usage of machine learning/AI tools in life science area(s) and handling life science datasets is preferred.
Excellent interpersonal, technical, and communication skills to lead cross-functional teams.
Profound grasp of Machine Learning lifecycle - feature engineering, training .
