Data Scientist, Quantitative Strategy

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Data Scientist, Quantitative Strategy

Company Overview

This organization is the leading agency driving national digital transformation and Smart Nation initiatives. As a center of excellence for infocomm technology and smart systems, the agency builds capabilities in data science, artificial intelligence, application development, smart city technology, digital infrastructure, and cybersecurity. Committed to innovation, the organization empowers its team with robust learning and development opportunities while delivering impactful solutions to enhance public service delivery.

Job Description

The organization seeks a Data Scientist for its Quantitative Strategy team to work on data projects and products for public good. This role focuses on identifying opportunities for data science applications, engaging stakeholders, and delivering actionable solutions that drive meaningful impact.

Key Responsibilities:

1. Facilitate discussions with stakeholders to understand business challenges, refine use cases, and translate them into data science projects/products.

2. Perform data cleaning, pre-processing, feature engineering, and build data science models/products to address use cases.

3. Present findings, solicit feedback, and refine analyses in close iteration with stakeholders, managing project timelines.

4. Communicate data insights and project outcomes in a clear narrative, supported by impactful visuals to influence decision-makers.

5. Design dashboards and interactive visualizations for data exploration and storytelling, as needed.

6. Deploy and monitor machine learning models using MLOps platforms, where applicable.

7. Collaborate with government agencies to build long-term data science capabilities, develop impactful projects, and operationalize solutions.

Key Requirements:

1. A Bachelor’s degree or higher in Data Science, Computer Science, Statistics, Economics, or related fields (certifications like Coursera are also considered).

2. At least 2 years of experience in data science or public sector roles.

3. Proficient in translating business use cases into analytical problems and identifying appropriate data sources.

4. Skilled in writing scripts, data preparation, and modern analysis tools and methodologies.

5. Experience with data cleaning, feature engineering, and ensuring high-quality datasets for analysis.

6. Expertise in statistical methodologies, machine learning models, and pattern recognition.

7. Strong skills in designing data visualizations and integrating them with real-time data systems.

8. Capable of delivering actionable recommendations and coherent data stories to stakeholders.

9. Passion for leveraging analytics to improve public services and deliver public good.

Preferred Requirements:

• Experience in model deployment and MLOps.

• Strong stakeholder management and agile project management skills.

• Proven ability to develop capabilities in others.

Disclaimer:

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2. No Client Relationship: This company is not a client of SpringCube unless stated.

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