Digital Health R&D – Data Scientist – Data Analytics and Statistics

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world.

The DH R&D Data Scientist Data Analytics and Statistics role closely partners with the broader DH R&D team (most notably Sensor Lab, Medical, and Clinical Operations), cross-functional scientists and colleagues, stakeholders and third-party providers to define, implement, and deliver digital measure outcomes  primarily for non-LY exploratory DH R&D trials via a key role in the Digital Health Innovation Hub being established in Singapore at the Lilly Centre for Clinical Pharmacology.   Purposes of the role include:

• Develops or assists in the development of DHT trial protocol designs, clinical plans, and data analysis plans in collaboration with physicians, and/or medical colleagues.

• Responsible for working with DHR&D broader team to analyze, report and readout data for DHT studies and DHT impacts in LY trials.

• Influence team members regarding appropriate research methods

Primary Responsibilities:

The job tasks listed below outline the scope of the position. The application of these tasks may vary, based upon current business needs.

DHT Trial Design and Analysis

• Operate in collaboration with study personnel to provide input on study protocol, design studies and write protocols for the conduct of each study, from statistical analyst point of view.

• Assist in or be accountable for selecting statistical methods for data analysis, authoring the corresponding sections of the protocol, and conducting the actual analysis.

• Collaborate with data management in the planning and implementation of data quality assurance plans.

• Maintain currency with respect to statistical methodology, to maintain proficiency in applying new and varied methods, and to be competent in justifying methods selected.

• Participate in peer-review work products from other statistical colleagues (AADS, GSS, and LY trial project stats team).

Communication of Results and Inferences

• As a Data Scientist, manage study analytics planning, tracking, and facilitation. Assist the development of DHT trial protocol designs, drive the data analysis plans, coordinate with cross-functional teams to define scope, timelines, and deliverables, while ensuring high quality data analytics for DHT study portfolio.

• Provide strong leadership in the process of DHT development, by preparing databases, statistical summary table/figures in accordance with a schedule.

• Collaborate with DHR&D team members to write reports and communicate results.

• Assist with, or be responsible for, communicating study results via reports, manuscripts, or oral presentations in group settings, as well as for communicating one-on-one with key customers and presenting at scientific meetings.

• Assist in response to regulatory queries and/or to interact with regulators from statistical analyst point of view.

Collaboration and Continuous Improvement

• Collaboration and Insight Development: Partner with internal and external SMEs to troubleshoot issues and work with data engineers to effectively leverage curated data, translating complex datasets into actionable insights.

• Continuous Improvement: Proactively identify and implement enhancements in data processing efficiency, integrity, and quality with a sharp eye towards elevating the standards of our data handling practices in DHT trials

Algorithm Development and Testing

• Rigorously test and validate the performance of developed algorithms across various datasets, ensuring their accuracy and reliability in real-world applications. This involves fine-tuning models for specific use cases, such as daily activity recognition and sleep detection, to enhance the overall effectiveness of sensor-based digital health technologies.

What You Should Bring

• Understand disease states in order to enhance the level of customer focus and collaboration and be seen as a strong scientific contributor.

• Demonstrated communication, leadership, teamwork, project delivery, and problem solving skills.

• Demonstrated ability to influence IT and business strategies to drive large-scale outcomes.

• Validated skills of strong learning agility and relationship building to influence change using knowledge and relationships.

• Successful record of high quality, user focused, on-time service and project delivery.

• Excellent analytical, problem solving and communication skills, working across agile and diverse teams. 

• A high level of intellectual curiosity, external perspective, and innovation interest.

• Demonstrated ability to communicate with a geographically dispersed group of business and technical colleagues.

Minimum Qualification Requirements:

• M.S. or Ph.D. in Statistics or Biostatistics or equivalent (Analytics, Informatics, Computer Science) with more than 5 Years of relevant experience

• Strong programming skills, and knowledge of data structures and algorithms – Python/R, SQL.

• Technical growth and application with working knowledge of experimental design and statistics.

• Excellent software development experience and problem solving skillsets

• Self-management skills with a focus on results for timely and accurate completion of competing deliverables

• Teamwork and leadership skills

Other Information/Additional Preferences:

• Demonstrated ability to effectively partner/influence a team and drive a technical project to deliver results

• Experience with application of data skills such as data flow, data quality & integrity, data interchange, data mining, and data representation principles

• Understanding and experience in Time Series Analysis, Generative AI, prompt engineering, and Large Language Model (LLM).

• A growth mindset and willingness to pick up new programming languages, technologies, and domain knowledge to be productive in role

Location: Singapore

Time Type: Full time

Job Type: Regular

Travel: 0-10% travel required

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.

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