Data scientist associate
Lensa is a career site that helps job seekers find great jobs in the US. We are not a staffing firm or agency. Lensa does not hire directly for these jobs, but promotes jobs on LinkedIn on behalf of its direct clients, recruitment ad agencies, and marketing partners. Lensa partners with DirectEmployers to promote this job for Takeda Pharmaceuticals. Clicking "Apply Now" or "Read more" on Lensa redirects you to the job board/employer site. Any information collected there is subject to their terms and privacy notice.
By clicking the “Apply” button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda’s Privacy Notice and Terms of Use . I further attest that all information I submit in my employment application is true to the best of my knowledge. Job Description Data Scientist Associate OBJECTIVES/PURPOSE We are seeking skilled, proactive and motivational Data Scientist who have good hands-on experience in data wrangling, transformations, building data-driven insights and statistical models. As part of the PDT DD&T (Plasma Derived Therapies Digital, Data & Technology) team, you will leverage advanced analytics to deliver data-driven solutions and insights that drive impactful business outcomes. Collaborating with cross-functional teams including R&D, Pricing, Marketing, Forecasting, you will analyze datasets, build predictive models, deploy and operationalize solutions to enhance organizational performance. Working closely with fellow data scientists on the team, as well as other team members from the Enterprise Data Science Community of Practice to advance best practices and knowledge sharing. You will report directly to the Data Science Lead, who will provide strategic direction. How You Will Contribute- Assist Data Science team members in addressing complex problems, conducting data analysis, and developing cutting-edge analytics solutions tailored to business needs.
- Translate business processes and requirements into actionable solutions by thoroughly understanding analytics drivers and data to be modeled, applying the most suitable quantitative techniques to solve challenges effectively.
- Design, develop, deploy, and operationalize advanced statistical methods, data science techniques, and Artificial Intelligence (AI/ML) solutions to enhance and optimize business operations.
- Monitor, evaluate, and refine data, analytics models, and experiments periodically to validate hypotheses, ensuring alignment with evolving business goals and continued delivery of value.
- Collaborate closely with cross-functional teams to embed data-driven insights into business strategies, processes, and operations, fostering data-centric decision-making across the organization.
- Guarantee the seamless, efficient, and timely delivery of statistical, data science, and AI/ML solutions, ensuring they meet high-quality standards and drive measurable impact.
- Design, develop, and implement decision-support solutions leveraging advanced statistical methodologies, data science/machine learning (ML), and a variety of quantitative techniques (e.g., simulations, mathematical modeling, etc.) to address complex business challenges effectively.
- Create and maintain code and processes that enable the operationalization of data-driven solutions, seamlessly aligning with the daily operational needs of the business.
- Acquire a comprehensive understanding of data sources and structures. Collaborate with the IT development team to strategize, design, and establish processes for data collection, ingestion, and delivery, along with developing optimal data models to fulfill analytical requirements.
- Engage with business stakeholders to identify pain points, articulate problem statements, define scope, and build data analytics business cases. Propose and develop tailored solutions underpinned by strategic data modeling and state-of-the-art data science techniques.
- Work closely with cross-functional teams, including GenAI/Agentic AI developers, to embed data-driven insights into business workflows and decision-making processes, harnessing AI-BI capabilities for enhanced operational efficiency.
- Provide analytical insights to support business solution development and implementation, influencing solution design and driving improved customer experiences.
- Design and deliver comprehensive analytics solutions by adhering to the complete lifecycle of statistical and AI/ML processes, ensuring the timely production of high-quality, impactful deliverables.
- Solid understanding of current and emerging AI/Advanced Analytics technologies. Expertise in the areas of Data, Data Modeling, Statistical Methods, Quantitative Techniques, and AI/ML preferred.
- Familiarity with Analytics processes and service models.
- Strong business acumen with knowledge of healthcare and retail operations.
- Provide guidance to junior team members and novice business users.
- Strong collaborating skills and experience in people management and skills development.
- Proven track record of making the right decision to resolve issues and obstacles.
- Self-motivated and self-directed in driving results and deliverables.
- Demonstrated success in the areas of global business and IT relationship, vendor management, and governance.
- Leverage advanced technologies such as AI/ML and effective statistical models to drive business results.
- Harvest enterprise analytics platforms and tooling to support BI solutions.
- Supporting PDT Functions in Americas, and Europe.
- High multicultural sensitivity in order to be effective.
- Ability to achieve results through remote collaboration.
- Bachelors’ Degree, from an accredited institution in Data Science, Statistics, Applied Mathematics, Physics, or other quantitative fields (master’s degree preferred).
- Minimum of 1 - 3 years of solid experience in statistics, quantitative methods (e.g. math modelling, simulation, etc.) and AI/ML/Data science experience in Life Sciences, Pharma, Biotech, technology companies or relevant regulated industries.
- Solid understanding of applied statistical and math modeling, and ML techniques (e.g. Clustering, Classification, Regression, Dimensionality Reduction, Ensemble Methods, Natural Language Processing.
- In depth experience in Python, PySpark, or R for data curation, transformation, analysis, modeling, and visualization tasks.
- Experience in a matrix organization collaborating with different teams including data engineering, enterprise architecture, platform architecture, and other application teams.
- Excellent written and verbal communication skills including the ability to interact effectively with multifunctional teams.
- 401(k) with company match and Annual Retirement Contribution Plan
- Tuition reimbursement Company match of charitable contributions
- Health & Wellness programs including onsite flu shots and health screenings
- Generous time off for vacation and the option to purchase additional vacation days
- Community Outreach Programs
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