BUSINESS EDGE PERSONNEL SERVICES PTE LTD Hiring! Full Time Data Engineer (Pharma) 1 YR Contract in Central Region (Singapore), Earn up to SGD 10,500 - Ricebowl

Connecting Patients and Technology:

This Data Engineer role offers the unique opportunity to connect a passion for patients, clinical development and technology by contributing to the data engineering, data analysis, and AI/algorithm development activities in clinical studies to passively and objectively measure disease-relevant physiology in support of company's drug development and it's digital health products, as well as driving new software products and AI-powered features for Company's Sensor Cloud (i.e., Magnol. Ai platform). In this role, you will also be engaged with developing and validating digital biomarkers and ultimately digital measures, which can have significant regulatory, patient and clinical trial impact. The role is based in the Digital Health Innovation Hub being established in Singapore at the Company for Clinical Pharmacology.

Purpose of the Role:

The Data Engineer is responsible for the data infrastructure that carries digital health technology (DHT) and wearable sensor data from collection through to analysis-ready datasets, as well as trial-level digital device data strategy including acquisition, storage, retrieval, interchange, delivery and representation.

This requires an in-depth understanding of wearable sensor data collection, dataflow, data quality, data technology, dataset delivery, archiving and data standards.

This role partners with study teams from the earliest stages of study design, builds and operates the pipelines that move and process sensor data at scale, and maintains the automated quality checks that keep that data sound, traceable, and reproducible. It applies advanced data analysis tools and techniques to provide insights and actionable recommendations for the trial, utilizes algorithms to derive clinically meaningful digital measures, and explains findings to business audiences. The role also contributes to the team's ongoing research and automation efforts, applying new data, AI, and compute technologies to extend what company's digital health platform can do.

The Data Engineer closely partners with the broader Digital Health team (most notably Sensor Lab 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 Digital Health trials.

Primary Responsibilities:

•    Support the early-stage design of digital health technology (DHT) studies, working with study teams to understand study objectives, the physiological signal the study is designed to detect, and the practice a realities of collecting data that will support that hypothesis.

•    Design and Implementation: Lead the design, construction, and optimization of systems for data collection, data transformation, and quality verification for company's proprietary data sets and metadata.

•    Use your architecture and programming skills to develop and implement data processing pipelines, data quality reporting, and pipeline monitoring resources for data ingestion and delivery of our proprietary data sets and machine learning outputs. The role encompasses end-to-end work such that the ideal candidate will have experience following raw data from ingestion all the way through to a completed feature data set prior to model scoring.

•    Serve as a primary developer on the team's pipeline code, covering data movement, processing, aggregation, quality control, and the integration of AI capabilities.

•    Algorithm development and testing: Apply heuristic algorithms, machine learning, and/or deep learning to develop new digital measures from sensor-based digital health technologies, e.g., daily activity recognition from continuous accelerometer / gyroscope data, sleep detection from Electroencephalography(EEG) and/or photoplethysmogram (PPG) data. Participate in model and algorithm development activities in a variety of areas including novel wearables, sleep detection, 3D environment reconstruction, and modern compute/GPU approaches for generating insights at scale.

•    Innovation with AI and LLM: Design, develop, and test new software features for the next- generation sensor cloud (Company's Magnol. Ai platform). This includes new software products for the platform and the integration of LLMs to enhance Magnol. Ai data analysis capability for personalized medicine.

•    Track the flow of DHT and Company's clinical trial data through the team's pipelines, monitoring study progress against expectations and flagging issues such as wear compliance, device malfunctions, or other emerging data problems.

•    Manage data flow and storage at scale, maintaining an organized structure for raw and processed data and replicating it to wherever it needs to be accessed.

•    Maintain and improve the team's automated data-quality-check systems, using them to catch issues early and drive root-cause analysis across studies.

•    Ensure every pipeline run is tracked as an independent, fully-documented artifact with complete metadata, so results can be traced, reproduced, and audited.

•    Build and maintain internal platforms and APIs that expose curated pipeline data to AI tools and assistants used across the team, and configure and manage the compute infrastructure that supports the team's AI-driven research and model development.

•    Partner with the team's data science and statistics group to analyze study data and help identify the best path forward for each study.

•    Collaboration and Interpretation: Work closely with our internal and external SMEs to troubleshoot issues, as well as with our data scientists and analysts to efficiently utilize our curated data, and translate 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.

•    Contribute to internal discussions shaping how company uses digital health technologies and wearables in both in-clinic and at-home research.

•    Stay current on relevant academic research and contribute to publications produced by the team.

•    Present the team's work to other groups within company, and at external events when appropriate, with an emphasis on clear, audience-appropriate storytelling.

Minimum Qualification Requirements:

•    Master's or PhD degree in Computer Science, Data Engineering, Analytics, AI, Informatics, or a related technical field, with at least three years of professional experience in data engineering, data analysis, and/or algorithm development.

Candidates with a Bachelor's degree and equivalent professional experience will also be considered.

•    Strong programming skills in Python and SQL, with hands-on experience building and maintaining production data processing pipelines.

•    Knowledge of data structures and algorithms, along with general familiarity with machine learning and deep learning methods.

•    Experience with cloud computing platforms(e.g., Azure, AWS, or GCP) and modern data engineering tools, including working knowledge of cloud architecture fundamentals and web security protocols.

•    Working knowledge of relational and non-relational database technologies and data modeling practices.

•    Demonstrated ability to identify data quality issues and build automated checks to catch and resolve them.

•    Excellent software development experience and strong problem-solving skills.

Other Information/Additional Preferences:

•    Experience working with wearable sensor data, time-series data, or other high-frequency data streams.

•    Understanding and experience in time series analysis, generative AI, prompt engineering, and large language models (LLMs).

•    Experience building, refining, or productionizing machine learning models, particularly for classification original / time-series data (e.g., activity or sleep detection).

•    Experience integrating AI or large language models (LLMs) into data platforms or applications.

•    Peer-reviewed publications, conference contributions, or other evidence of research output in a relevant area.

•    Demonstrated ability to set and implement plans to develop sensor-based digital health technology.

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

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

•    Experience in a regulated industry, such as healthcare, life sciences, or clinical research, is a plus.

•    Strong written and verbal communication skills, with the ability to present technical work to both technical and non-technical audiences.

•    A collaborative, growth-oriented mindset and willingness to pick up new tools, languages, and domain knowledge as the role requires.

Interested Parties please WhatsApp/Call us at ************* (Jasmine), and email your latest resume in WORD format to ************* You may call my office number at 65698233 (Ext.839) for a private & confidential discussion. EA License No.: 96C4864 Reg No.: R22108682 Lee Yit Foong Jasmine