Data Scientist – Digital Health & Sensor Data Analytics

InnoCellence; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

InnoCellence is seeking a Data Scientist to derive insights from clinical study sensor data and develop algorithms for real-time processing. You will collaborate with customers to analyze data and build models to address business problems in digital health.

The role emphasizes ML algorithm development, time-series analysis, and deployment of AI solutions including prompt engineering and RAG pipelines. Strong communication and cross-functional collaboration are essential.

Qualifications

• Ph.D. in Computer Science, Statistics, Mathematics, or related field.
• 3+ years of experience in data science with sensor data or digital health.
• Strong understanding of time-series analysis, signal processing, and feature extraction.
• Proficiency in Python or R with ML libraries.
• Hands-on experience with big data platforms (Hadoop, Spark) and cloud environments.

Responsibilities

• Collaborate with customers to identify key questions and test hypotheses with clinical study data.
• Develop and implement ML algorithms for processing and interpreting sensor data (accelerometers, heart rate monitors).
• Design and implement solutions using LLMs and Generative AI, including prompt engineering and RAG pipelines.
• Apply preprocessing to large sensor datasets, handling noise and missing data.
• Validate results for accuracy, performance, and scalability in real-time processing.
• Communicate findings with stakeholders through visualizations, reports, and presentations.
• Work with cross-functional teams to develop data-driven solutions.
• Stay updated with data science and clinical research advancements.

Skills

Time-series analysis

Python

R

ML/AI

Data visualization

Education

PhD in CS/Stats/Math

Tools

TensorFlow

PyTorch

Hadoop

Spark

Cloud platforms

Job description

We are seeking a talented and experienced Data Scientist to join our team. The ideal candidate will be passionate about utilizing data science methodologies to derive insights from digital device sensor data coming from clinical studies and contribute to the development and implementation of algorithms in this area. As a Data Scientist, you will work closely with customers to analyze data and build models and tools that enhance understanding of clinical outcomes and solve their business problems.

Responsibilities:

• Collaborate with customers to identify key questions, develop hypotheses, and test those hypotheses with clinical study data.
• Develop and implement machine learning algorithms for processing and interpreting sensor data (e.g., accelerometers, heart rate monitors, etc.). Research and develop novel digital measures with clinical significance.
• Design, develop, and implement solutions leveraging Large Language Models (LLMs) and Generative AI technologies, including prompt engineering, model fine-tuning, and Retrieval-Augmented Generation (RAG) pipelines.
• Apply data preprocessing techniques to optimize large sets of sensor data processing and analysis, handling issues like noise, missing data, and time-series synchronization.
• Validate and interpret results to ensure accuracy, performance and scalability in real-time processing of sensor streams.
• Communicate findings and insights to stakeholders through clear and compelling visualizations, reports, and presentations.
• Work closely with cross-functional teams to develop data-driven solutions to address business needs.
• Stay up-to-date with the latest advancements in data science and clinical research to continuously improve methodologies and approaches.

Requirements:

• Ph.D. in Computer Science, Statistics, Mathematics, or related field.
• 3+ years of experience in data science, with a focus on sensor data analysis or digital health.
• Strong understanding of time-series analysis, signal processing, and feature extraction techniques.
• Proficiency in programming languages and libraries (e.g, Python/R, TensorFlow/Pytorch) for data analysis and machine learning.
• Hands-on experience with big data platforms and tools (e.g., Hadoop, Spark, cloud environments).
• Strong problem-solving and analytical skills.
• Excellent communication and collaboration skills with the ability to work effectively in a team environment.

Preferred Qualifications:

• Familiarity with cloud-based deployment platforms such as AWS, Azure or related and their data pipeline development.
• Experience working in the healthcare or pharmaceutical industry, particularly in clinical trials or digital health devices.
• Proven experience in taking algorithms from research to production, including considerations for scalability, performance, and ease of integration.
• Understanding of clinical trial workflows and regulatory requirements related to digital health.