Data Scientist, Client Consultant (Contract)

ARGYLL SCOTT CONSULTING PTE. LTD.; Singapore; Vor Ort; SGD 90.000 - 150.000; Vollzeit

Zusammenfassung

ARGYLL SCOTT CONSULTING PTE. LTD. is seeking a Data Scientist to support a leading financial institution in Singapore on a 12-month contract.

The role focuses on analysing transaction, customer behavior, and banking portfolio data to generate actionable insights and drive portfolio profitability. You will translate complex analyses into commercial recommendations, executive reporting, and strategic opportunities, while collaborating with senior leadership and business stakeholders to support

Qualifikationen

• Bachelor's or Master's degree in Data Science, Statistics, CS, Maths, Economics, Engineering, or related quantitative field.
• 5+ years of experience in advanced analytics, BI, or analytics consulting with large datasets.
• Proficiency in Python and SQL with strong statistical analysis skills.
• Experience with ML, predictive modelling, and customer segmentation techniques.

Aufgaben

• Analyse large-scale transaction and portfolio data to identify revenue growth and profitability opportunities.
• Perform customer lifecycle analysis including acquisition, activation, spending, retention, and value management.
• Evaluate portfolio trends and merchant spending to identify market opportunities.
• Translate findings into practical business recommendations for product strategy, marketing and loyalty initiatives.
• Develop dashboards and executive reports covering portfolio performance, trends, and risk indicators.
• Establish KPIs and reporting frameworks to support strategic planning and reviews.

Kenntnisse

Data analysis

Statistical methods

Communications

Ausbildung

Bachelor's or Master's in quantitative field

Tools

Python

SQL

Power BI

Tableau

Jobbeschreibung

Data Scientist, Client Consultant (Contract)

Location: Singapore

Contract Type: 12 months contract (Extendable & Convertible)

Keywords: Data Science, Python, SQL, Payments Analytics, Portfolio Analytics, Customer Segmentation, Predictive Modelling, Power BI, Tableau, Machine Learning

Role Overview

A global payments technology organisation is seeking a Data Scientist to support a leading financial institution in Singapore. The role focuses on analysing transaction, customer behaviour, and banking portfolio data to generate actionable insights, improve portfolio performance, and support strategic business decisions. Working closely with business stakeholders and senior leadership, the successful candidate will translate complex analytical findings into commercial recommendations, executive-level reporting, and opportunities to improve customer engagement and portfolio profitability.

Key Responsibilities

• Analyse large-scale transaction and portfolio datasets to identify opportunities for revenue growth, customer engagement, portfolio optimisation, and profitability improvement.
• Conduct detailed analysis across the customer lifecycle, including acquisition, activation, spending behaviour, retention, attrition prevention, and customer value management.
• Evaluate portfolio trends, customer behaviour, merchant spending patterns, and market opportunities at both individual market and group levels.
• Translate analytical findings into practical business recommendations supporting product strategy, customer acquisition, marketing investments, loyalty initiatives, and portfolio management.
• Develop management dashboards, strategic performance reports, business reviews, and executive presentations covering portfolio performance, emerging trends, growth opportunities, and risk indicators.
• Establish key performance indicators (KPIs) and performance measurement frameworks to support strategic planning, performance monitoring, and business reviews.
• Automate recurring reporting and analytical processes, while developing reusable analytical resources, reporting templates, and frameworks to improve efficiency and scalability.
• Engage senior business stakeholders to understand commercial challenges, establish analytical priorities, and present findings and recommendations to support decision-making.

Job Requirements

Essential Requirements

• Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, Economics, Engineering, or a related quantitative discipline.
• Minimum 5 years of experience in advanced analytics, data science, business intelligence, or analytics consulting, with demonstrated experience analysing large datasets and generating business insights.
• Advanced proficiency in Python and SQL, with strong statistical analysis skills and knowledge of analytical methodologies.
• Experience with statistical modelling, machine learning, predictive modelling, and customer segmentation techniques.
• Proficiency in data visualisation and reporting tools, including Power BI or Tableau, Excel, and advanced reporting applications.
• Experience using generative AI tools or platforms in an analytical or professional environment.
• Demonstrated ability to develop executive-level presentations, management reports, and clear data-driven recommendations.
• Strong commercial awareness, analytical rigour, strategic problem-solving, stakeholder management, and communication skills, with the ability to manage client deliverables and communicate complex findings to senior audiences.

Preferred / Advantageous Requirements

• Experience in financial services, payments, retail banking, or credit card portfolio analytics.
• Familiarity with issuer portfolio analysis, customer lifecycle management, and cardholder behaviour analytics.
• Experience working independently as an individual contributor, including structuring analytical problems, leading analytical workstreams, and delivering outputs with minimal supervision.
• Experience collaborating with banking data teams or working within a banking environment.
• Previous experience in a client-facing consulting role.
• Knowledge of banking datasets, including cards, deposits, loans, transaction flows, customer behaviour, and credit or risk-related information.
• Understanding of payment networks, merchant analytics, and transaction data ecosystems.
• Exposure to cloud-based analytics platforms.