Sensor Data Scientist - Digital Health & AI Insights

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

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.