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Data Scientist - Job Opportunity at FOCAL SEARCH PTE. LTD.

Singapore, Singapore
Full-time
Mid-level
Posted: July 7, 2025
On-site
SGD 80,000 - 120,000 per year (USD 60,000 - 90,000). This estimate reflects Singapore's competitive data science market, where mid-level professionals with machine learning expertise command premium salaries due to high demand and the city-state's position as a regional technology hub. The range accounts for the comprehensive skill set required, including proficiency in multiple programming languages, advanced ML frameworks, and business communication capabilities.

Key Responsibilities

Develop advanced statistical models, machine learning algorithms, and predictive analytics that directly drive strategic business decisions and competitive advantage through data-driven insights
Transform complex, multi-dimensional datasets into actionable intelligence that enables executive-level decision-making and operational optimization across business units
Design and execute sophisticated experimental frameworks to validate hypotheses and measure model performance, ensuring statistical rigor and business relevance in all analytical outputs
Partner strategically with data engineering and analytics teams to architect robust data pipelines that support scalable, enterprise-level data science initiatives
Communicate complex analytical findings to C-suite executives and key stakeholders through compelling data visualizations and presentations that translate technical insights into business value

Requirements

Education

Bachelor's or Master's degree in mathematics, statistics, computer science, or a related subject

Experience

Not specified

Required Skills

Proficient in Python or R Strong SQL skills and knowledge of database structures Experience using machine learning libraries like scikit-learn, TensorFlow, or PyTorch Proficiency in visualization tools such as Tableau, Power BI, and matplotlib Capability to manage unstructured data and complex data difficulties Excellent communication and teamwork abilities
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Sauge AI Market Intelligence

Industry Trends

The Asia-Pacific data science market is experiencing unprecedented growth driven by digital transformation initiatives across financial services, e-commerce, and manufacturing sectors, with Singapore positioning itself as the regional hub for AI and machine learning innovation. Organizations are increasingly investing in predictive analytics capabilities to gain competitive advantages in market forecasting, customer behavior analysis, and operational efficiency optimization. There is a significant shift towards MLOps and production-ready machine learning systems, with companies moving beyond proof-of-concept models to scalable, enterprise-grade solutions that can handle real-time data processing and automated decision-making. This trend is particularly pronounced in Singapore's fintech and logistics sectors, where rapid deployment of ML models directly impacts business performance. The integration of large language models and generative AI into traditional data science workflows is creating new opportunities for advanced analytics, particularly in natural language processing applications for customer insights, automated reporting, and intelligent data exploration. Singapore's strategic position as a technology hub makes it a prime location for companies adopting these cutting-edge technologies.

Role Significance

Typically operates within a 5-8 person data science team, collaborating closely with 2-3 data engineers, 3-4 business analysts, and reporting to a senior data science manager or head of analytics. The role involves mentoring junior team members while receiving strategic direction from senior leadership.
This role represents a core contributor position within the data science hierarchy, requiring independent project leadership and strategic thinking beyond entry-level execution. The emphasis on stakeholder communication and cross-functional collaboration indicates expectations for influencing business strategy and driving organizational data maturity. The position serves as a bridge between technical execution and business impact, requiring both deep technical expertise and strategic business understanding.

Key Projects

Development and deployment of customer lifetime value prediction models that inform marketing strategy and budget allocation across multiple channels and customer segments Implementation of real-time fraud detection systems using ensemble machine learning methods, processing millions of transactions daily with sub-second response times Creation of demand forecasting models for supply chain optimization, integrating external data sources including weather patterns, economic indicators, and market sentiment analysis Building recommendation engines that personalize customer experiences across digital platforms, utilizing collaborative filtering, content-based filtering, and deep learning approaches

Success Factors

Ability to translate complex business problems into well-defined analytical frameworks, demonstrating strong problem decomposition skills and understanding of how data science solutions create measurable business value Proficiency in end-to-end model development lifecycle, from data exploration and feature engineering through model validation, deployment, and monitoring in production environments Strong stakeholder management capabilities, including the ability to communicate technical concepts to non-technical audiences and build consensus around data-driven decision-making processes Continuous learning mindset to stay current with rapidly evolving machine learning techniques, tools, and industry best practices, particularly in emerging areas like MLOps and responsible AI

Market Demand

Very High - Singapore's data science market is experiencing acute talent shortages as organizations across finance, technology, and government sectors accelerate their AI and analytics initiatives. The demand significantly exceeds supply, particularly for professionals with production ML experience and strong business acumen.

Important Skills

Critical Skills

Python/R proficiency is absolutely essential as these languages form the foundation of modern data science workflows, with Python particularly valued for its extensive ecosystem of machine learning libraries and integration capabilities with production systems. Mastery of these languages directly impacts productivity and the ability to implement sophisticated analytical solutions. Machine learning framework experience (scikit-learn, TensorFlow, PyTorch) is crucial for implementing state-of-the-art models and staying competitive in the rapidly evolving ML landscape. These frameworks represent the industry standard for both research and production machine learning applications. SQL and database knowledge are fundamental for data extraction, manipulation, and analysis in enterprise environments where data scientists must work with complex, multi-table datasets stored in various database systems. Strong SQL skills directly correlate with efficiency in data preparation and exploratory analysis. Data visualization capabilities using tools like Tableau, Power BI, and matplotlib are essential for communicating insights effectively to stakeholders and ensuring that analytical findings translate into actionable business decisions.

Beneficial Skills

Cloud platform expertise (AWS, Azure, GCP) is increasingly valuable as organizations migrate their data science workflows to cloud environments, enabling scalable model deployment and collaborative development practices MLOps and model deployment skills are becoming essential as the industry shifts focus from model development to production deployment, monitoring, and maintenance of machine learning systems Domain-specific knowledge in finance, healthcare, or e-commerce can provide significant competitive advantages by enabling more contextually relevant analytical solutions and faster project delivery Advanced statistical knowledge and experimental design capabilities are valuable for roles requiring rigorous hypothesis testing and causal inference, particularly in companies with strong research orientations or regulatory requirements

Unique Aspects

The role emphasizes both traditional statistical modeling and modern machine learning techniques, suggesting an organization that values analytical rigor alongside innovation in emerging technologies
Strong focus on stakeholder communication and data visualization indicates a business-centric approach to data science, where technical excellence must be paired with effective business communication
The requirement for managing unstructured data and complex data challenges suggests involvement in cutting-edge projects that go beyond standard analytics, potentially including natural language processing, computer vision, or IoT data analysis
Cross-functional collaboration with data engineers highlights the importance of production-ready solutions rather than research-oriented projects, indicating a mature data science practice focused on business impact

Career Growth

Progression to senior roles typically occurs within 2-3 years with demonstrated impact on business outcomes and technical leadership. Management track positions generally require 3-5 years of experience plus proven leadership capabilities.

Potential Next Roles

Senior Data Scientist positions focusing on technical leadership and advanced modeling techniques, typically involving architecture of complex ML systems and mentoring of junior team members Data Science Manager roles combining technical expertise with people management, budget oversight, and strategic planning for data science initiatives Machine Learning Engineer positions emphasizing production deployment, model monitoring, and MLOps infrastructure development Principal Data Scientist or Staff Data Scientist roles in larger organizations, involving cross-functional leadership and enterprise-wide analytics strategy

Company Overview

FOCAL SEARCH PTE. LTD.

FOCAL SEARCH PTE. LTD. operates as a specialized recruitment and talent acquisition firm serving the Singapore and broader Southeast Asian market, with particular expertise in placing technology and data science professionals. The company has established itself as a trusted partner for both multinational corporations and local enterprises seeking to build their analytics capabilities.

As a boutique recruitment firm, FOCAL SEARCH maintains strong relationships with leading technology companies and emerging startups across Singapore's vibrant tech ecosystem. The company's focus on specialized roles like data science positions it well in the competitive talent acquisition market, where deep domain expertise is essential for successful placements.
Singapore serves as the company's primary operational hub, providing access to one of Asia's most dynamic technology markets. The location offers significant advantages for talent acquisition, given Singapore's role as a regional headquarters for many multinational corporations and its growing reputation as a fintech and AI innovation center.
The recruitment industry demands high performance and results-oriented approaches, suggesting a dynamic work environment with emphasis on relationship building, market knowledge, and client service excellence. Professionals in this sector typically experience fast-paced, client-focused cultures with strong emphasis on business development and networking.
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