Total 56 data entry job vacancies in Others category

•You will be responsible for end-to-end delivery of enterprise data and analytics solutions leveraging traditional and modern Data architecture. Experience with Financial Crime Analytics, Finance & Credit Risk Analytics, Credit Scoring & Decision systems, Retail & Wholesale Datamarts will of advantage

•The role spans requirements analysis, solution design, testing, implementation, and production support ensuring high-quality, scalable, and compliant data platforms that support advanced analytics and AI initiatives.

Key Responsibilities

•Lead end-to-end solution delivery for data and analytics across the full SDLC.

•Analyze business and regulatory requirements, translate them into scalable solution designs & provide estimations.

•Communicate complex technical and architectural concepts to business and senior stakeholders in a clear, simplified manner.

•Review and approve test strategies, functional test cases, and data validation approaches.

•Manage risks and issues related to scope, data quality, regulatory commitments, and delivery timelines.

•Participate in product and platform evaluations (RFPs, PoCs) for data, analytics, and AI tooling.

•Partner with production support team to conduct root cause analysis, resolution, and preventive controls.

•Lead innovation and modernization initiatives, including data discovery, cataloguing, governance, and AI enablement.

•Drive productivity, efficiency & quality improvements across delivery and operational processes.

•Ability to design data architectures supporting NLP and AI-driven analytics.

FUNCTIONAL SKILLSETS

Analytics Domains

•Financial Crime Analytics Transaction Monitoring, Customer Due Diligence, Sanctions & Payments Screening

•Finance & Credit Risk Analytics Financial reconciliation, Allocation, Performance management, Regulatory and Management reporting, Credit risk exposure, NPL, Counterparty risk, Basel & IFRS9 input variables

Enterprise Data, Analytics & Unstructured Data Enablement

•Proven experience delivering large-scale analytics platforms within financial services spanning structured, semi-structured, and unstructured data

•Strong capability in requirements analysis and functional design for analytics use cases involving Transactional data, Investigator narratives, Case notes and alerts, Policy & Customer communications documents

•Experience defining data quality, governance, lineage, and reconciliation controls for both structured and NLP-derived datasets.

Unstructured Data & NLP-Enabled Analytics

•Ability to define data architectures and data flows that ingest, curate, and govern unstructured and semi-structured data within enterprise data platforms.

•Experience translating business requirements into NLP-enabled analytical use cases, such as Text classification and categorization, Entity & relationship extraction, Risk indicator identification, Summarization of alerts, cases, or documents

Knowledge Graph & Relationship Based Analytics

•Ability to design and govern an enterprise knowledge layer defining relationship taxonomies, entity resolution rules, and linkage logic

•Ability to translate use cases into relationship driven analytical designs, such as Network based risk identification, Hidden association and indirect exposure analysis, Related party and concentric risk detection

Requirements

Data Platforms & Architecture

•Open table formats: Apache Iceberg, Delta Lake, Apache Hudi

•Distributed processing & query engines: Spark, Trino/Presto, Hive

•Cost optimization strategies: tiered storage, lifecycle management, workload governance

Programming & Analytics

•SQL, BTEQ, GCFR

•Python (Pandas, NumPy)

•BI & visualization tools: Power BI, QlikSense

Data Integration & Quality

•Informatica suite: PowerCenter, BDM, IDQ, Enterprise Data Catalogue

•Data ingestion patterns: batch, CDC, streaming

•Data validation, quality controls, and reconciliation frameworks within environments

Governance, Risk & Compliance

•Data modelling, critical data elements, regulatory reporting

•Fine-grained data access controls (row-level, column-level, masking)

•Metadata management, lineage, and impact analysis

•Compliance with BCBS 239, MAS, AML/CFT, and internal data standards

Big Data Platforms

•Cloudera Hadoop distribution: Hive, Impala, Spark, Iceberg, Trino

The Opportunity

A global owner-operator of mission-critical infrastructure is seeking a Regional Commissioning Director to lead commissioning strategy and execution across its Asia Pacific portfolio.

This role is designed for a senior commissioning leader ready to transition from project-level delivery into regional ownership, setting standards, improving repeatability, and driving long-term operational efficiency across multiple large-scale developments.

You will work closely with development, engineering, delivery, and operations teams to ensure consistent, high-quality commissioning outcomes across diverse regulatory and technical environments.

Key Responsibilities

• Lead regional commissioning strategy for large, mission-critical facilities across APAC

• Manage internal commissioning teams and external consultants across multiple countries

• Establish and govern commissioning standards, methodologies, and best practices

• Oversee commissioning planning, sequencing, and execution for complex, multi-phase developments

• Drive continuous improvement initiatives to enhance delivery efficiency and reduce risk

• Support procurement activities related to commissioning services and critical systems

• Review commissioning scopes, schedules, and budgets to ensure alignment with project objectives

• Conduct design and constructability reviews in collaboration with engineering and delivery teams

• Ensure effective coordination between commissioning, construction, and operations for smooth handover

• Act as a senior stakeholder interface for internal teams, delivery partners, and customers

• Promote a strong safety, quality, and compliance culture across all commissioning activities

Candidate Profile

• Degree in Mechanical, Electrical, or Building Services Engineering (or equivalent experience)

• 7+ years of experience in mission-critical commissioning, complex infrastructure delivery, or facility engineering

• Prior experience leading commissioning activities across multiple projects or regions

• Strong understanding of MEP systems and integrated systems testing in critical environments

• Experience working across diverse regulatory and cultural environments in Asia Pacific

• Familiarity with structured commissioning management tools and digital workflows

• Proven ability to lead teams, manage consultants, and influence senior stakeholders

• Clear, confident communicator with strong commercial and delivery acumen
  

  Why Join

  • Regional leadership role with genuine influence over how commissioning is delivered at scale

  • Exposure to large, complex infrastructure developments across high-growth APAC markets

  • Opportunity to shape standards and frameworks that will be reused across future projects

  • Long-term career growth within a well-capitalised, expanding platform

• How to Apply Click Apply now or send your resume directly to Talent@BuildBridgePartners.com
  

  
  
  

  
  
  

  EA Name: BuildBridge Partners Pte Ltd

  EA License No: 25C2918

  EA Reg No: R1551092 Khoo Yan Jie

The Rail Digitalisation Division is a cross-functional andmulti-disciplinary team set up to drive and deliver LTA’s Railway CommonData Platform (CDP), which includes data analytics and artificialintelligence capabilities to support rail performance andoperational/maintenance enhancements. You will be responsible for building the"intelligence layer" of the CDP, developing systems that not onlydetect anomalies in complex railway time-series data but also reason about themto provide clear, actionable outcomes for maintenance and operations.

We are seeking a Senior Data Scientist who excels at convertinguse cases into a data problem and analyzing data to generate value to supportdecision making. You should have a proven track record of deliveringend-to-end machine learning solutions—from data discovery and featureengineering to model deployment and monitoring. The ideal candidate balancesdeep technical expertise with a value-driven mindset, ensuring that analyticaloutputs directly translate to better cost efficiency and improved commuter experience.A degree in Data Science, Statistics, Computer Science, Engineering, or arelated quantitative field is required.

Technical Skills

• Modeling & Time-Series Analysis: Expert proficiency in Python and SQL. Deep experience in time-series forecasting and anomaly detection (e.g., Z-score, growth rate analysis, and statistical thresholds).
• Data Engineering Synergy: Competence with modern data stacks (e.g., Snowflake, Databricks) and real-time data ingestion via APIs to build scalable, production-ready pipelines.
• MLOps & Automation: Experience in managing the full ML lifecycle, focusing on "operational AI" that triggers automated workflows or maintenance alerts.
• Visualization & UI Collaboration: Ability to translate complex model outputs into requirements for UI/UX designers to create intuitive, data-rich enterprise dashboards.
• Decision Intelligence: Proven ability to build autonomous systems that go beyond simple detection, including experience with AI agents that combine statistical triggers with LLM-based reasoning to automatically categorise, prioritise, and/or escalate operational issues.

Key Attributes

• Analytical Problem Solver: Strong ability to take vague operational "pain points" and structure them into rigorous analytical frameworks that drive ROI.
• Stakeholder Management: Exceptional communication skills to explain algorithmic logic and "uncertainty" to non-technical stakeholders.
• Proactive Learner: A self-starter who stays updated on the latest in Agentic AI and can independently drive design initiatives end-to-end.
• Collaborative: High comfort level working in a "squad" format alongside UI/UX designers, Product Managers, and Railway Engineers.

Requirements

• Background knowledge in Computer Engineering, Data Science, Statistics, Computer Science, Engineering, Business and Commerce or a related quantitative field is required.
• At least 5 years of relevant experience in data science, preferably with data-heavy industrial or enterprise products.
• Experience in transportation, IoT, or large-scale condition-monitoring systems with AI agents is advantageous.
• Successful candidates may be expected to undertake technical assessments or case study presentations as part of the interview process.

As part of the shortlisting process for the role,you may be required to complete a medical declaration and / or undergo furtherassessment.

Tired of retail, hospitality, admin—or just stuck in a routine that doesn’t excite you anymore? This could be your reset button.

Your Role:
• Represent exciting client campaigns through face-to-face interactions
• Deliver a positive, professional, and memorable customer experience
• Work closely with a driven team to hit shared goals
• Level up your communication and people skills through structured training

What We’re Looking For:
• Attitude over experience
• Eagerness to learn and grow
• Strong communication and a team-first mindset

Why You’ll Love It Here:
• Full hands-on training (we build you up from day one)
• High-energy, supportive team culture
• Real career progression—not just promises, but pathways

If you’re ready for something more dynamic, this is your sign to step in and start building your next chapter.