Lead Data Scientist

**Description**

Headquartered in Singapore, **Actxa** Pte Ltd is a deep tech company founded in 2015 that leverages artificial intelligence to create next generation preventive healthcare solutions.

We create evidence-based, personalised health insights in the domains of physical activities, sleep quality, body composition, stress and recovery, heart health and blood glucose evaluation and monitoring.

To improve population health, Actxa establishes worldwide partnerships and research collaborations to develop critical preventive health models to help people avert chronic diseases such as diabetes and hypertension.

We believe in positively impacting the lives of people around us and the environment we live in through the use of technology. Hence, we are committed to providing a conducive environment for all employees to realise their full potential, who in turn have the opportunity to continuously drive innovation.

We have opportunities for you to grow your career path and are looking for talented professionals to join our team.

We are seeking a passionate and visionary Lead **Data Scientist **to lead our data science efforts in shaping the future of healthcare in preventive health using **Artificial Intelligence** (AI), **Machine Learning** (ML) and **data analysis**. Your work will directly contribute to improving the health and well-being of the population, reducing healthcare costs, and championing a proactive approach to healthcare.

In this managerial-level role, you will drive the company’s technology solutions and research initiatives. You are responsible for leading and managing a team of Data Scientists and Researchers in delivering science and data-driven innovations in preventive health and population wellness.

This role requires you to have prior experience in end-to-end solutions deliveries from research to implementation involving Artificial Intelligence, data analysis, Machine Learning (ML), data analysis and statistical modeling.

**Actxa** is hiring for **Lead Data Scientist**
- Internal Code: AC152_

**Data Analysis and Modeling**:

- Utilize advanced statistical techniques, artificial intelligence and machine learning algorithms to analyze complex datasets.
- Develop predictive and prescriptive models to achieve business and commercial goals.
- Explore and identify patterns, trends, and anomalies in data.
- Lead, mentor, and manage a team of data scientists and researchers.
- Provide guidance and direction for project planning, execution, prioritization and documentation.
- Foster a collaborative and innovative team culture.

**Team Leadership**:
**Research Strategy**:

- Define research objectives, strategies, and roadmaps in alignment with organizational goals.
- Stay updated with the latest developments in data science and research methodologies.
- Identify emerging technologies and tools that can enhance research capabilities.
- Establish research partnership and collaboration with local and overseas institutions.

**Data Collection and Preparation**:

- Oversee data acquisition, cleaning, and preprocessing.
- Ensure data quality and integrity to maintain the accuracy of analyses.
- Collaborate with data engineering teams to streamline data pipelines.

**Experimentation and Hypothesis Testing**:

- Design experiments and conduct hypothesis testing to validate research findings.
- Evaluate the effectiveness of various models and methodologies.
- Implement A/B testing and other statistical methods to drive decisions.

**Cross-functional Collaboration**:

- Collaborate with consultants, advisors and internal teams, such as software & hardware solution, sales, marketing, and operations, to address business challenges and commercialisation opportunities.
- Provide data-driven recommendations and insights to support decision-making in clinical research projects.

**Ethical Data Practices**:

- Ensure compliance with data privacy regulations and ethical data handling practices.
- Maintain the security and confidentiality of sensitive data in clinical research studies.

**Project Management**:

- Manage multiple research projects simultaneously, including resource allocation and timelines.
- Monitor project progress, identify risks, and implement mitigation strategies.

**Continuous Improvement**:

- Drive process improvements and best practices in data science and research.
- Evaluate and implement new tools and technologies to enhance research capabilities in clinical research studies.

**Requirements**:

- Advanced degree (Ph.D. or Master's) in a relevant field such as Computer Science, Data Science, Statistic, Mathematics, Biomedical Engineering, Electrical & Electronics Engineering, or related discipline.
- Several years of experience in artificial intelligence, data analysis, statistical modeling, and machine learning with strong programming skills in languages such as **Python**, **R*, **SQL* and **C/C++**:

- Excellent communication and leadership skills.
- Ability to think c