Total 963 data entry job vacancies in Information Technology category

Job Title: Data Analyst (Tableau | BI | Govt | 12 months)
Duration: 12 months
Salary Package: 3000-3450
Location: Mapletree Business City
Eligibility: Only Singaporean

Overview
The project is to build up "the company" capability in business intelligence (BI), particularly in the data analysis and developing insights on "the company's" grant recipients and projects. The temp will perform data cleansing activities on grant data, develop data pipeline on Government cloud, implementing enterprise Tableau dashboard, and establishing machine learning model.

Responsibilities

• Ensure deliverables and milestones are completed on time and on target
• Perform data extraction, transformation and load activities from existing systems/reports
• Develop and maintain enterprise Tableau reports
• Develop new python scripts and maintain existing scripts for analysis of high-risk grants
• Maintain documentation on data assets, architecture, transformation, and tools

Qualifications

• At least Bachelor’s degree in Data Analytics / Computer Science or equivalent 
• Hands-on with Tableau Desktop, Tableau Prep Builder, Tableau Server
• Goal-oriented, meticulous, and able to work independently 
• Guidance is provided, but you must be hands-on and unafraid to pick up new technical skills on the go 
• Available Immediately

Apply Now via MyCareersFuture
Only Qualified Candidates are Contacted

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In Ref: SS – JO-28279 - C
BGC Group Pte Ltd (Outsourcing)
EA 05C3053

Job Purpose:

The Assistant Manager, Data Management Centre (SSC), supports HR Shared Services by overseeing accurate data processing, maintaining compliance with audit and policy requirements, and ensuring timely delivery of employee-related transactions. The role leads a team in managing SAP data integrity, partners with internal stakeholders, and drives workflow improvements to enhance service quality and operational efficiency.

What You’ll Do:

• Lead & Oversee Daily Operations: Motivate and guide a team of officers to meet Service Level Agreements (SLAs) with Business Partners and deliver reliable HR data services.

• Manage HR Data & System Transactions: Ensure accurate, timely input of employee and company data in SAP, aligned with audit, compliance, and confidentiality requirements.

• Collaborate with Key Stakeholders: Work closely with Payroll, Business Units, GHR, and IS teams to support pay runs, address queries, and implement policy or system changes.

• Drive Process Improvements: Identify gaps, conduct root-cause analysis, streamline procedures, implement enhancements, and update SOPs and training materials.

• Support Governance & Reporting: Handle employee data requests, prepare reports, respond to audit queries, and ensure data integrity for internal and external stakeholders.

What You’ll Bring:

• Education & Experience:  Bachelor’s degree in business, Information Systems, or a related discipline — or a Diploma with 1–2 years of relevant experience, preferably in a Shared Services environment.

• Systems Knowledge: Hands-on experience with SAP or an equivalent HR Information System is an advantage.

• Communication Skills: Good oral and written communication skills, with the ability to interact professionally with stakeholders.

• HR Domain Knowledge: A thorough understanding of HR practices, policies, and procedures.

• Professional Attributes: Detail-oriented, discreet with sensitive data, and able to work both independently and in a team-based setting.

As the Head of Data Analytics at our leading AI company focused on self-developed multimodal large language models (LLMs), you will lead our data analytics team to drive end-to-end data strategy, governance, and insight generation across the entire lifecycle of our multimodal model R&D and commercialization. You will be responsible for building a robust AI-focused data analytics framework, leveraging advanced data science and machine learning techniques to transform raw multimodal data into actionable business and technical insights, and aligning data initiatives with the company's strategic growth goals. This role is critical to optimizing our multimodal model performance, accelerating product iteration, and enabling data-driven decision-making across all business functions.

Key Responsibilities

1. Develop and implement analytics techniques and applications to transform raw multimodal data (text, image, audio, video) into valuable insights using data programming languages and visualization tools.

2. Apply data mining, data modeling, NLP, and machine learning methods to extract and analyze information from large-scale structured and unstructured datasets.

3. Visualize, interpret, and present data insights and dynamic dashboards to technical and business stakeholders to support R&D and commercial decisions.

4. Lead, mentor, and scale the data analytics team; establish workflows, standards, and best practices for data governance, quality, and model evaluation.

5. Collaborate with AI research, engineering, and product teams to design data pipelines, evaluation metrics, and A/B testing frameworks for multimodal model improvement.

6. Oversee data collection, cleansing, labeling, and validation processes to ensure high-quality data assets for model training and fine-tuning.

7. Drive data-driven decision-making across the organization and align data initiatives with company AI strategy.

Qualifications

1. Master’s degree or higher in Engineering, Computer Science, Data Science, Information Technology, Statistics, Mathematics, or a related field.
2. Minimum 5+ years of professional experience in data science, data analytics, or a closely related role, with at least 2+ years in a leadership or managerial position.
3. Demonstrated experience working in AI, large language models, multimodal models, machine learning, or deep learning research/engineering environments.
4. Proficiency in data-oriented programming languages (Python, SQL), big data tools, and data visualization software.
5. Strong knowledge of machine learning, statistical analysis, data mining, NLP, and multimodal data processing.
6. Experience building and managing data teams, defining data strategies, and implementing data governance frameworks.
7. Excellent communication, presentation, and stakeholder management skills.

Position: SAP Data Analyst / SAP Master Data Executive (1-Year Contract)

Job Description:

• Hands-on experience working with SAP

• Strong knowledge of SAP Master Data, including Material Master Data and Vendor Master Data

• Perform data analysis and validation to ensure data accuracy and integrity

• Proficient in Excel, including Power Query

• Ability to work independently with minimal supervision

• Apply critical thinking to interpret data and make sound recommendations based on analysis

Work Location: Tuas
Contract Duration: 1 year
Salary: up to 4k

Interested candidates, do submit your resume to: jocelynchan@recruitexpress.com.sg OR telegram @jocelynchan

Jocelyn Chan| Consultant | Recruit Express Pte Ltd (Healthcare & Lifescience)
Company EA Licence number : 99C4599
Personnel EA License: R1331820

Job Description: Lead Data EngineerRole OverviewWe are looking for a Lead Data Engineer to design, build, and scale our data automation and ingestion capabilities. This role will play a critical part in shaping how data is collected, processed, and operationalized across the organization.You will lead the development of scalable, reusable data collection and processing systems using Python-based pipelines, APIs, and workflow-driven automation primarily focussing on data automation, pipeline reliability, and production-grade model execution.This is a hands-on role for an experienced data engineer who enjoys building robust systems, improving standards, and partnering closely with analytics, backend, UI, and data operations teams.Key ResponsibilitiesData Ingestion & AutomationDesign and develop scalable, reusable data ingestion systems using Python, APIs, web scraping, and file-based ingestion.Build and maintain data collection methods for diverse data types and sources, including APIs, Excel, flat files, HTML etc.Ensure ingestion pipelines are automated, fault-tolerant, and self-healing, minimizing manual intervention.Pipeline Integration & ExecutionIntegrate ingestion pipelines with enterprise data storage and processing layers.Leverage Decisions (workflow automation software) and internal workflow services to orchestrate and execute data transformation and manipulation workflows.Partner with internal platform and workflow teams to ensure pipelines run consistently at scale.Data Quality, Governance & StandardsDefine and enforce data quality checks, validation rules, and reconciliation logic across pipelines.Ensure strong data governance and cross-system alignment, working closely with backend, analytics, and UI teams.Establish and promote development standards, including Script and module structure, Logging, error handling, Unit testing and validation frameworksReduce technical risk and future rework through consistent engineering practices.Model Operationalization & Data Ops EnablementWork closely with Data Ops and Analytics teams to help transition Python-based models from: Analyst-led prototypesTo production-ready, scalable, and reliable operational modelsEnsure models can be executed efficiently within workflow-driven environments (e.g., Decisions), with proper dependency management, performance optimization, and monitoring.Enable end-to-end execution of data pipelines and models, supporting growing data volumes and increased execution frequency.Provide Technical leadership, Guiding design decisions, reviewing code and architectureRequired Skills & ExperienceSenior-level data engineer (typically 10+ years), with strong hands-on experience and the ability to lead and shape systems rather than just implement tasks.Strong hands-on experience with Python in production data engineering environments.Proven experience building data ingestion pipelines, ETL/ELT-style processes, and automation frameworks using code (not GUI-based tools).Strong knowledge of data manipulation and scraping libraries, including Pandas, NumPy, Requests, BeautifulSoup and Selenium (or similar browser automation tools)Experience working with APIs, authentication mechanisms, and structured/unstructured data formats.Solid understanding of data quality, validation, and governance practices.Experience designing pipelines that are Scalable, Reliable, Idempotent, Easy to monitor and debugFamiliarity with workflow-based execution and orchestration concepts.Strong ability to collaborate across teamsAbility to translate analytical needs into robust, production-grade data solutions.

Role Overview 

The Data Engineer / Data Scientist will be responsible for designing, developing, and maintaining data pipelines, performing data analysis, building predictive models, and ensuring data quality across platforms and operations. 

Responsible for extracting insights and value from complex datasets by applying statistical analysis, machine learning, and data visualization techniques. The role involves collaborating with business stakeholders to understand problems, developing predictive and prescriptive models, and communicating findings to support data-driven decision-making. Data Scientists work closely with data engineers and AI teams to operationalize models and ensure actionable outcomes. 

Key Responsibilities 

- Design, build, and optimize scalable data pipelines and ETL processes. 

- Develop and maintain data models, data marts, and analytical datasets. 

- Collaborate with cross-functional teams to gather requirements and deliver data-driven solutions. 

- Perform exploratory data analysis (EDA) and create machine learning models as required. 

- Implement data quality checks, validation rules, and monitoring processes. 

- Automate data workflows and ensure timely availability of data. 

- Work with cloud platforms such as Azure, AWS, or GCP for data engineering activities. 

Technical Skills 

- Proficient in programming languages such as Python or R 

- Expertise in statistics, machine learning algorithms, and data mining techniques 

- Experience with data preprocessing, feature engineering, and model validation 

- Skilled in data visualization tools and libraries (Tableau, Power BI, Matplotlib, Seaborn) 

- Familiarity with big data platforms (Spark, Hadoop) and SQL databases 

- Knowledge of cloud-based ML platforms (AWS SageMaker, Azure ML, GCP AI Platform) 

- Understanding of experimental design and A/B Testing 

- Ability to communicate complex technical concepts to non-technical stakeholders 

Key Responsibilities (non-exhaustive) 

- Analyze large and diverse datasets to identify trends, patterns, and insights 

- Develop, train, and validate predictive and classification models 

- Analyze and select the appropriate AI foundation models for use where appropriate 

- Design experiments and conduct hypothesis testing to support business initiatives 

- Collaborate with data engineers to prepare and optimize data for analysis 

- Translate analytical findings into clear, actionable recommendations 

- Present insights and reports to stakeholders using visual storytelling techniques 

- Monitor and maintain models in production environments to ensure ongoing accuracy 

- Stay updated on emerging tools, techniques, and best practices in data science 

Quality Testing Responsibilities 

- Develop and execute data validation and data quality test cases. 

- Perform unit and integration testing for data pipelines. 

- Monitor data accuracy, completeness, and consistency across systems. 

- Identify data anomalies and work with engineering teams to resolve issues. 

- Document test results and maintain testing logs. 

Preferred Qualifications 

- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field. 

- 3–5 years of experience in data engineering, data science, or related domains. 

- Hands-on experience with SQL, Python, and distributed data systems. 

- Knowledge of machine learning techniques and statistical analysis. 

- Experience with cloud data platforms (Azure Data Factory, AWS Glue, GCP BigQuery). 

- Familiarity with DevOps practices and CI/CD for data pipelines. 

Platforms & Operations Experience (Preferred) 

- Experience working with Azure, AWS, or Google Cloud data tools. 

- Operational experience with data orchestration tools (Airflow, ADF, Glue). 

- Understanding of Kubernetes, Docker, or containerized environments. 

- Hands-on experience with data warehousing platforms (Snowflake, Redshift, BigQuery). 

- Experience in monitoring, logging, and alerting operations for data workflows. 

• Plan and execute marketing initiatives for AI data center and immersion cooling solutions.
• Create professional content: presentations, solution briefs, case studies, and digital/LinkedIn materials.
• Drive local campaigns, webinars, and events to generate leads and strengthen client engagement.
• Collaborate closely with sales and technical teams to develop customer-facing materials and proposals.
• Represent the company professionally at client meetings and industry events.

Requirements:

• Degree in Engineering, IT, Marketing, Business, or equivalent
• At least 5 years of B2B marketing experience in data centers, IT infrastructure, AI/GPU platforms, or cooling solutions.
• Solid understanding of data center operations, rack layouts, cooling technologies, and GPU-based AI systems.
• Ability to translate technical concepts into clear value propositions for non-technical stakeholders.

If you are keen to apply for the position, kindly email your detailed resume in MS Word to hr@recruit-expert.com

Please note that only shortlisted candidates will be notified.

For more job opportunities, please visit our website at www.recruit-expert.com

EA Licence: 19C9701

Registration: R1326740

• Min 4-6 years in related field.
• Experience in managing data reconciliation/quality checks by SLA (implementation, monitoring and troubleshooting).
• Able to handle data issue management.
• Good in handling dynamic project tasks in an data warehouse transformation project.
• Proficient in SQL.
• Experience in designing and executing UAT.
• Able to manage user requests and queries.
• Provide documentation support in technical/functional specifications.
• Possess investment data domain knowledge.
• Good problemsolving and logical thinking.

This role entails data analysis for both CDE & Incentive management function in providing thorough analysis and insights in providing timely decision making and strategies. It also plays a major role in the automation and digitalization of both CDE & Incentive data. It ensures data accuracy and creates an efficient reporting tool for CDE function. He/She requires to work on improving the current data & reporting system in CDE working with key stakeholders to improve and ensure effectiveness and efficiency in tracking and monitoring ALL CDE equipment to protect and sweat company’s assets. He/She will be the key person in working on OU initiative for all CDE matters related to piloting new initiatives and adopt best practices in other market to bring CDE data and reporting up to Global standard of OU Cooler Playbook.

COMMUNICATION COMPLEXITIES:

• Channel Lead – Placement & Productivity reports tracking for respective region, Automation of CRF form for daily request by sales team
• Channel Lead – review on monthly penetration & productivity reports also to provide insights and review the Incentive KPIs result to ensure incentive KPIs set were effective where they are achievable and yet challenging
• PowerBI – working closely with Digital Team & Vendor IT side to understand their data flow to be integrated and automate CDE & Incentive data
• CDE Support team – working close to create and improve SOPs, moving away from manual to automation
• Finance Team – working closely to ensure efficiency of the coolers deployed and recommendation on cooler deployed that needed to be pull out if they are not productive
• OU – working with OU team in the local projects related to CDE initiative and innovation, to dive into the benefit of IOT and explore innovation to bring in and optimizing coolers output

Above list is not exhaustive and only highlights the main communication requirements with cross-functional stakeholders

ANALYSIS:

The role is very crucial in ensuring ALL CDE equipment are well manage, monitor and track. Ensure that ALL CDE assets are properly use and well taken care to ensure maximum ROI of our assets. This position is crucial to support the on-going expansion plan especially in GT Channel. Perform analysis on incentive & commission ensure that it’s within the budget. Coordinating with stakeholders and assisting line manager with to Incentive analysis.

Judgment and Decision Making:

• Cooler placement at Top Industry stores (Recommender)
• Productivity of Our Assets (Recommender)
• Data management and system enhancement (Final Authority)
• Dashboard creation and data flow (Final Authority)
• Data integration to enhance reporting capability (Final Authority)

Innovation: List duties for creating/changing processes, systems, products

· CDE Dashboards – Penetration, Productivity, Cooler Tracking & Cooler IOT

· Incentive Dashboards – Budget vs Spending, KPI effectiveness & Target setting

TOS Auto Group is a growing automotive company with three core divisions — car sales, spray paint, and workshop services.

We are looking for a Data Entry Assistant to support our administrative and record-keeping operations across all three entities.

Job Responsibilities

• Input, update, and maintain data for sales, workshop, and spray paint transactions
• Ensure data accuracy and consistency across all three entities (TOS Auto, TOS Auto SprayWerk, and TOS MotorWerk)
• Organize bills, invoices, and receipts in both digital and physical formats
• Prepare and file supporting documents for accounting and reporting purposes
• Coordinate with the admin and accounts team for monthly data verification
• Perform other general administrative duties as assigned

Requirements

• Basic computer literacy (Microsoft Excel, Word, Google Sheets)
• Strong attention to detail and good organizational skills
• Able to handle repetitive tasks accurately and efficiently
• Prior experience in admin or data entry is an advantage
• Team player with good communication and time management skills

What We Offer

• Friendly and supportive work environment
• Exposure to car sales, spray paint, and workshop operations
• Working hours: Monday to Friday, 9.30am - 6.30pm

NIPSEA Group is a global leader, providing innovative solutions in the paint and coatings industry. Headquartered in Singapore, with more than 134 NIPSEA companies spread throughout 22 geographical locations, the group is Asia Pacific’s No. 1 paint and coatings manufacturer in both production and sales revenue. After more than 60 years of growth, NIPSEA Group has over 27,000 employees with 102 manufacturing facilities and operations, efficiently serving all aspects of the business, from production to customer satisfaction. With a focus on maximizing value to our customers, we push boundaries to deliver high-quality solutions that work better for all our partners, tradesmen, and homeowners. The NIPSEA Group’s arsenal of solutions for the industry covers Architectural, Industrial, Automotive and Marine Coatings, as well as a range of products beyond the world of paint and coatings. We have an unyielding drive to focus noncustomers, providing innovation that works best for all our stakeholders.

To support our data science and AI efforts, we are seeking a Data Analyst / Data Scientist who has strong knowledge and expertise in data science, AI, machine learning, deep learning, generative AI and agentic AI, has at least 1-3 years of experience with implementing data science and AI projects in a dynamic business environment. Strong fresh graduates will also be considered. Successful candidates will work in a highly collaborative environment with internal and external stakeholders across different functional areas and business units. Candidates who additionally have experience with paints and coatings, chemistry or materials science are preferred.

Roles& Responsibilities

• Implement and manage data science and AI projects throughout their lifecycles to meet business and technical needs
• Train, validate, test and deploy data science and AI models using on-premise and cloud resources
• Extract, transform, load and visualize data from various sources across the company indifferent geographical regions
• Gather and translate business and technical needs from internal and external stakeholders into metrics that can be optimized by data science and AI models
• Collaborate closely with domain experts (e.g. chemists), IT engineers, software engineers, technology leaders and business leaders to ensure that data science and AI projects will meet business and technical needs
• Prepare presentations and reports on data science and AI project outcomes to facilitate management’s decision-making and strategic planning
• Keep abreast of latest developments and trends in data science and AI and implement innovative data science and AI models and best practices timely
• Enthusiastic about learning relevant domain knowledge of paints and coatings that is needed to successfully execute data science and AI projects

Requirements

• Bachelor’s or master’s degree in computer science, AI, data science, electrical engineering, statistics, mathematics or related fields
• Strong knowledge and expertise in data science, AI, machine learning, deep learning, generative AI, agentic AI
• At least 1 – 3 years of experience with implementing data science and AI project sin a business environment. Strong fresh graduates will also be considered.
• Proficient in programming e.g. Python, SQL
• Proficient in using machine learning frameworks e.g. PyTorch, TensorFlow, Keras, scikit-learn, MLOps
• Capable of working independently as well as in teams
• Excellent communication skills for presentations and reports
• Proficient in written and spoken English
• Experience with paints and coatings, chemistry or materials science is a plus
• Able to travel occasionally as and when required.

Responsibilities

IT Helpdesk & Corporate Support (~20%)

·       Provide Level 1 IT support for Corporate Office users (~35 users)

·       Manage user provisioning, device setup, access rights, and asset tracking

·       Troubleshoot common issues (M365, endpoints, printers)

·       Escalate complex infrastructure issues to central IT or vendors

·       Maintain structured ticket logs and monthly support reporting

Data Governance & Quality (~20%)

·       Support structured data quality assessments across corporate and plant systems

·       Coordinate with data owners to maintain master data integrity

·       Maintain enterprise data standards, dictionaries, and validation rules

·       Support digitization of manual data capture processes

·       Identify and document systems of record for key operational data

·       Work on digitization of data

Process Automation (~40%)

·       Document and map repetitive/manual processes across plants and corporate functions

·       Identify and prioritize automation opportunities

·       Develop and maintain low-code/RPA workflows

·       Test, deploy, and monitor automation performance

·       Maintain automation inventory and quantify efficiency gains

·       Track and report time savings and error reduction

·       Continuously refine deployed automations

Applied AI / ML Support (~20%)

·       Prepare structured datasets for AI/ML use cases

·       Perform exploratory data analysis (EDA)

·       Manage and maintain ETL/ELT pipelines for centralized data preparation

·       Support development, testing, and monitoring of predictive/prescriptive models

·       Document model performance and improvement opportunities

Qualifications & Skills

Education

·       Degree in Information Systems, Computer Science, Data Analytics, or related field

Technical Skills

·       Working knowledge of SQL, Python or R

·       Familiarity with JavaScript, HTML, CSS (basic level)

·       Experience with Power BI or similar visualization tools

·       Exposure to low-code automation tools (Power Automate, UiPath, etc.)

·       Understanding of data governance and data lifecycle principles

·       Strong documentation discipline

Helpdesk Technical Skills

·       Windows 10/11 troubleshooting

·       Microsoft 365 administration and support

·       Email configuration and troubleshooting

·       End-user device and peripheral support

·       Basic network connectivity troubleshooting

·       User and access management

·       Shared drive and permission management

This role covers the activities post inputs are received from the source - retailers/vendors. Primary focus is to be the bridge between the Supplier Engagement team and other Ops pillars. System changes surveys, BAU query resolution, MSD tickets tracking and closure, KPIs reporting, productivity initiatives, RCAs are the key areas of work for this team. Apart from this, the team is also responsible to analyze, classify and management of the data. This role is accountable for handling data queries arising from BAU quality checks (RAP & DQI scoring).

Job Responsibilities

Retailer Onboarding and Engagement:

• Collaborate with the Supplier Engagement Lead on retailer onboarding.
• Ensure compliance for received data by working closely with retailers and NielsenIQ teams.
• Track retailer or vendor data quality and conduct regular reviews with internal stakeholders and retailers.
• Drive specific quality improvement goals for retailers, including change management related to data receipt.
• Handle large data sets with exposure to multiple formats and TLog data.
• Understanding of SAP, transactional data handling, FTP, and MFT setup and maintenance.
•  Ability to extract, transform, load, and clean large data sets from multiple sources.
• Familiarity with managing, querying, and aggregating large data sets.

System Change and Data Corrections:

• Plan and follow up on operational activities.
• Address data corrections due to MSD or other data errors through retailer discussions and planning with Ops.
• Track and resolve MSD tickets.
• Collaborate with INS team on results of eDive for System change.

Stakeholder Management & BAU Collaboration and Communication:

• Act as the internal SPOC for Ops and regional leadership teams.
• Provide updates on KPIs, market progress on retailer onboarding, BAU KPIs, and productivity initiatives. (internal SPOC for Ops)
• Communicate with internal and external stakeholders to resolve data issues.
• Provide timely updates and visibility to stakeholders.
• Contact data providers via email if data has not been received as per SLAs.
• Communicate with data providers on any discrepancies found in initial data checks, FoVa reports, shop usability, or other factory processes.
• Handle new store information and confirmation on store closures.
• Address new stores and closed store queries.
• Coordinate with Input Ops and Output for processing reissued data.
• Send relevant IO communications (internal) regarding new/closed stores, missing retailer data, estimation of retailer data, reissue of retailer data, store name changes, store mapping corrections, retailer expansion, and retailer data changes during BAU.

Quality Assurance:

• Conduct quality checks, including eDive primary testing of data, and RAP scoring, eDive.
• Address data queries arising from quality checks.

Opportunity Identification:

• Identify new operational efficient opportunities within existing retailers.
• Ops teams (NOC), and DA Analysts to realize these opportunities, consulting closely with the commercial or RV team as applicable.

Key Responsibilities:

• Monitor data center systems, servers, and network equipment.

• Perform routine checks on power, cooling, and environmental systems.

• Respond to alarms, incidents, and system alerts.

• Assist with hardware installation, replacement, and cabling.

• Maintain logs, reports, and operational documentation.

• Follow safety, security, and operational procedures.

• Coordinate with IT and facilities teams when issues arise.

Requirements:

• Basic knowledge of data center or IT operations.
• Ability to monitor systems and respond to incidents.
• Good communication and teamwork skills.
• Willingness to work in shifts, including nights and weekends.

Interested applicants please send your resume to venessagoh@recruitexpress.com.sg

Venessa Goh Wee Ni

R24124686

Recruit Express Pte Ltd

EA License No: 99C4599

We regret that only shortlisted candidates will be contacted.

The Reference Data Specialist (RD PH) is responsible for instructions of client deliverables, coding and data input validation focusing on specific industry/category or set of categories (e.g. Beverages, Food, Health and Beauty Products). As a Reference Data Specialist  at NielsenIQ, you create and deliver client outputs in a correct and timely manner.

• Responsible for instructions of client deliverables, coding and data input validation focusing on specific industry/category or set of categories.
• Does cross coding and item-related quality checks on a daily basis
• May act as a back-up to other coders when needed; conduct physical store check to validate item-related information
• Keep track/document special instructions related to category assignment
• Plan and execute a complex daily personal workload and support to meet departmental and company schedules
• Ensure accuracy throughout the process, from validation before database setup to managing samples, and identify areas for improvement
• Answer external questions and act as a liaison with everyone from clients to stakeholders; To be able to identify, investigate and coordinate the resolution of data, process, or product related queries
• Willing to be trained to be a category expert