Manager Finance Data Science

Becton Dickinson Medical (S) Pte Ltd; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

A leading global medical technology company in Singapore is looking for a Manager, Finance Data Science. This role involves utilizing AI and data analytics to provide insights that influence decision-making within the finance organization. The successful candidate will lead projects aimed at delivering predictive models and optimizing business processes. Candidates should have at least 7 years of experience, including expertise in Python, R, and machine learning techniques, along with a relevant degree.

Qualifications

• 7-9 years of overall experience and 4-5 years of relevant experience.
• Experience in Finance Data Science Use cases and deployment.
• Hands-on technical data analysis experience.

Responsibilities

• Research and implement statistical and ML models for predictive analysis.
• Develop and deploy data science and AI solutions.
• Collaborate with technology teams to implement analytical models into production.
• Communicate results and insights effectively to stakeholders.

Skills

Python

R

SQL

Machine Learning

AI frameworks (PyTorch, TensorFlow)

Data visualization (Tableau, PowerBI)

Cloud computing (AWS, Azure)

ETL tools (Informatica, Talend)

Statistical analysis

Data science cloud platforms

Education

Bachelor's/Master's in Statistics or related field

Degree in Finance (preferred)

Tools

Tableau

PowerBI

AWS

Azure

Data Bricks

Job description

Segment: Corporate Functions

Location: GA, Singapore

Unit: Finance

Position Title: Manager, Finance Data Science

Job Description: Manager, Finance Data Science

Job Description Summary

We are the makers of possible BD is one of the largest global medical technology companies in the world. Advancing the world of health™ is our Purpose, and it’s no small feat. It takes the imagination and passion of all of us—from design and engineering to the manufacturing and marketing of our billions of MedTech products per year—to look at the impossible and find transformative solutions that turn dreams into possibilities.

Why Join Us?

A career at BD means learning and working alongside inspirational leaders and colleagues who are equally passionate and committed to fostering an inclusive, growth-centered, and rewarding culture. You will have the opportunity to help shape the trajectory of BD while leaving a legacy at the same time. To find purpose in the possibilities, we need people who can see the bigger picture, who understand the human story that underpins everything we do. We welcome people with the imagination and drive to help us reinvent the future of health. At BD, you’ll discover a culture in which you can learn, grow and thrive. And find satisfaction in doing your part to make the world a better place. Become a maker of possible with us!

Job Summary

As a Manager Finance Data Science, you will be responsible for generating insights using cutting edge artificial intelligence, data science, and advanced analytics research and end to end project execution that influence decisions at various levels in the finance organization. This role is accountable for designing and delivering predictive and prescriptive analytics models by using large data sets and finding opportunities for improvement in business planning processes. You will lead and deliver projects and develop solutions that improve accuracy and create efficiencies.

Duties and Responsibilities

• Research and implement statistical and ML models for predictive analysis and decision support.
• Develop and deploy data science and AI solutions, including data processing, algorithm development, data visualization, and communication of insights to stakeholders.
• Develop data engineering pipelines for large datasets from finance/ERP systems and automate data science processes.
• Implement analytical models into production on the data science platform by collaborating with technology teams.
• Devise algorithms and models to mine big data stores, clean data for uniformity and accuracy, automate data collection and preparation process and analyze large data from big data platforms to discover trends and patterns.
• Communicate results and ideas to key decision makers and explain complex models in a simple manner.
• Iteratively improve the process and models to solve problems, testing and documenting changes, aligning changes within the team.
• Utilize machine learning algorithms to enhance financial analyses and improve forecasting accuracy.
• Conduct scenario analysis and sensitivity testing to evaluate potential financial outcomes and risks.
• Collaborate with cross-functional teams to integrate insights into financial planning and reporting processes.
• Present results to stakeholders through visualization tools and techniques.
• Monitor end to end integration of data science model from data gathering, data cleaning, production and integration with user systems and tools.
• Work on proof of concepts to solve a business problem in an agile manner.
• Collaborate with technology, engineering and Finance process teams.
• Keep up-to-date with latest technology trends like Generative AI.

Minimum Qualifications

• 7-9 years of overall experience and 4-5 years of relevant experience.
• Bachelor's/Master's in Statistics, Mathematics, Computer Science, Business Analytics, Finance or any quantitative field.
• Good to have a degree in Finance and/or working experience in Finance.
• Previous experience in Finance Data Science Use cases and deployment.

Skills Required

• Prior experience in at least one finance domain is preferred (FP&A, Tax, Treasury, Global Services etc).
• Experience Python, R, SQL to manipulate data and draw insights from large data sets.
• Proficiency in one or more AI frameworks such as PyTorch or Tensorflow.
• Experience in working with data science cloud platforms on AWS, Azure, Data Bricks etc.
• Hands‑on technical data analysis, cloud computing (AWS, Azure), and dockers is a plus.
• Knowledge of Alteryx/DataIKU, Tableau/PowerBI etc and good understanding of ETL tools and data pipelines.
• Experience in end-to-end implementation-taking model from proof of concept to production.
• Good understanding of ETL tools like Informatica, Talend etc.
• Experience with practical applications of machine learning techniques such as regression, decision trees, probability networks, association rules, clustering, neural networks, and/or Bayesian models.
• Experience with handling time series data.
• Continuous improvement mindset and critical thinking.
• Drive to learn and master new technologies and techniques.
• Experience with work prioritization and deadline changes.
• Good knowledge around risk management, compliance adherence and commitments.
• Experience working across multiple levels of business stakeholders, creating context around key business drivers and strategic plan.
• Good written and oral communication skills.

Primary Work Location

SGP The Strategy