Total 2 job vacancies by Innocellence Consulting Pte. Ltd.

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.
• 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:

• Hands-on experience with Large Language Models (LLMs) or Generative AI projects, such as prompt engineering, fine-tuning, or implementing Retrieval-Augmented Generation (RAG) pipelines
• 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.

We are looking for a skilled and experienced Data Science Engineer to join our team. The ideal candidate will be responsible for designing, building, and maintaining robust data pipelines to support the processing and analysis of clinical study and digital device sensor data. As a Data Science Engineer, you will work closely with data scientists and software engineers to ensure the efficient and reliable flow of data from source systems to analytical tools and platforms.

Responsibilities:

• Design, develop, and maintain scalable data pipelines to ingest, transform, and load clinical study data from various sources, including digital device sensors.
• Optimize data storage and retrieval processes in cloud-based platforms to ensure high performance and reliability.
• Collaborate with data scientists to integrate data processing pipelines with AI-powered algorithms and third-party analytical tools or platforms.
• Implement data quality checks and monitoring mechanisms to ensure the integrity and accuracy of the data.
• Troubleshoot and resolve issues related to data pipeline performance, reliability, and scalability.
• Work closely with software developers, system architects and other cross-functional teams to develop data-driven business solutions.
• Stay up-to-date with emerging technologies in AI & Cloud computing and best practices in data engineering to continuously improve data processing pipelines and infrastructure.

Requirements:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Proven experience in designing and building data pipelines using ETL tools and frameworks such as Apache Spark, Apache Beam, or Apache Airflow.
• Proficiency in programming languages such as Python, Java, or Scala.
• Strong understanding of database systems, data warehousing concepts, SQL and NoSQL.
• Experience with AI and Cloud Computing: Hands-on experience with cloud platforms like AWS and familiarity with AI solutions in these environments.
• Excellent problem-solving and troubleshooting skills with a strong attention to detail and quality.
• Effective communication and collaboration skills with the ability to work in a team environment.

Preferred Qualifications:

• Experience with containerization and orchestration tools such as Docker and Kubernetes.
• Familiarity with big data technologies such as Hadoop, Hive, or Presto.
• Knowledge of distributed computing frameworks such as Apache Hadoop or Apache Spark.
• Familiarity with ElasticSearch or AWS OpenSearch is plus
• Prior experience working with healthcare or clinical data is a plus.