Data Scientist

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

Job summary

InnoCellence in Singapore seeks a Data Scientist to derive insights from digital device sensor data collected in clinical studies and to develop and implement algorithms in this area. You will collaborate with customers to analyze data and build models that improve understanding of clinical outcomes and solve business problems.

The ideal candidate holds a PhD in CS/Statistics/Math or related field, with strong time-series analysis and signal processing skills, and proficiency in Python or R,

Qualifications

• Ph.D. in CS, statistics, mathematics, or related field.
• Demonstrated data science experience via research, internships, or roles; PhD work counts.
• Strong time-series analysis, signal processing and feature extraction knowledge.
• Proficiency in Python or R, and TensorFlow/PyTorch for ML.
• Excellent problem-solving, communication and teamwork skills.

Responsibilities

• Collaborate with customers to identify questions, form hypotheses, and test them with clinical study data.
• Develop and implement machine learning algorithms for processing and interpreting sensor data.
• Preprocess large sensor datasets, handling noise, missing data and time-series alignment.
• Validate results and ensure accuracy, performance and scalability in real-time processing.
• Communicate findings through visualizations, reports and presentations.
• Work with cross-functional teams to deliver data-driven solutions.
• Stay up-to-date with advances in data science and clinical research.

Skills

Time-series analysis

Signal processing

Communication

Collaboration

Education

PhD in Computer Science, Statistics, Mathematics, or related field

Tools

TensorFlow

PyTorch

Python

R

Job description

We welcome applications from PhD graduates at all career stages, including those completing or recently completing their doctoral degree. Research experience in relevant domains (clinical data science, wearable sensors, signal processing, digital health) is valued equally to industry experience.

We are seeking a 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.
• 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.
• Demonstrated experience in data science through research, internships, or professional roles. PhD research in relevant areas (signal processing, clinical data, wearables, time-series ML) counts towards this requirement. New graduates with strong PhD projects in these areas are encouraged to apply.
• 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.
• Strong problem-solving and analytical skills.
• Excellent communication and collaboration skills with the ability to work effectively in a team environment.

Preferred Qualifications

• Exposure to Large Language Models (LLMs) or Generative AI (including coursework, research exploration, prompt engineering, and early-stage project work).
• Familiarity with at least one of: Image/video analysis (computer vision) and Speech/audio processing.
• 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.