Senior Data Scientist

Short Summary

Senior Data Scientist with NielsenIQ. As a Senior Data Scientist, you will play a key role in developing end-to-end analytic solutions, shaping data and algorithms to deliver accurate and robust Predictive and Prescriptive Analytics. At NIQ, we’re looking for someone to join our Tech & Durable Global Data Science team, working at the intersection of business, data science and engineering to transform business problems into…

Key Details

• Position / opportunity: Senior Data Scientist
• Organization: NielsenIQ
• Country / coverage: Malaysia
• Location: Kuala Lumpur, 14, Malaysia
• Work arrangement: On-site
• Opportunity type: Volunteer opportunities
• Sector: Education
• Compensation: Not specified
• Duration: Not specified
• Start date: 2026-08-05
• Application deadline: Not specified

Description

As a Senior Data Scientist, you will play a key role in developing end-to-end analytic solutions, shaping data and algorithms to deliver accurate and robust Predictive and Prescriptive Analytics. At NIQ, we’re looking for someone to join our Tech & Durable Global Data Science team, working at the intersection of business, data science and engineering to transform business problems into robust, production-ready Data Science solutions. Your Mission: Build scalable, production-ready data science solutions that enable the use of or directly utilize NIQ's Tech & Durable Point-of-Sale data. Collaborate cross-functionally with product managers, engineers, designers and business stakeholders to translate complex problems into actionable insights. Contribute to the evolution of our data science ecosystem through innovation, mentorship, and thought leadership. Responsibilities: Perform research to drive the development of product focused Data Science solutions for our T&D business. Build, fine-tune and deploy state-of-the-art neural networks for Extreme Multilabel Classification problems. Ensure documentation, reproducibility and quality of code. Collaborate with MLEs and SREs to deploy models in live production pipeline Foster Data Science related knowledge exchange within NIQ (e.g. Lunch & Learns, Communities of Practice). Mentor and guide junior team members and working students, serving as a methodological expert and role model. Essential Skills: Degree in computer science, data science, statistics, or a related field. 5+ year experience in a Data Science role. Expert knowledge of developing and optimizing deep learning algorithms on GPU infrastructures using the PyTorch framework. Experience with fine-tuning third-party Large Language Models sourced from e.g. HuggingFace. Proven ability to ship large-scale models to production environments. Strong Python skills and familiarity with development tools (e.g. Jupyter, PyCharm, VSCode). Ability to think creatively in addressing analytical objectives. Strong presentation and data visualization skills (e.g., ability to communicate complex insights clearly to technical and non-technical audiences). Excellent stakeholder management and communication skills to align technical solutions with business needs. Ability to work independently and asynchronously as part of a distributed team Professional working proficiency in English Desirable Skills: Familiarity with the evolving data science ecosystem and popular machine learning frameworks beyond PyTorch (e.g. scikit, tensorflow). Experience with software engineering best practices (version control, testing, agile development, Scrum, Safe). Hands-on experience with cloud computing platforms (e.g. GCP) and productionizing machine learning models (e.g. expose as REST API, containerization, scalability, performance optimization). Benefits: • Exciting work environment that brings people together. • Use the latest digital technologies. • Ongoing trainings to support your development. • Opportunities for personal and professional growth. • Hybrid work Our Benefits Flexible working environment Volunteer time off LinkedIn Learning Employee-Assistance-Program (EAP) NIQ may utilize artificial intelligence (AI) tools at various stages of the recruitment process, including résumé screening, candidate assessments, interview scheduling, job matching, communication support, and certain administrative tasks that help streamline workflows. These tools are intended to improve efficiency and support fair and consistent evaluation based on job-related criteria. All use of AI is governed by NIQ’s principles of fairness, transparency, human oversight, and inclusion. Final hiring decisions are made exclusively by humans. NIQ regularly reviews its AI tools to help mitigate bias and ensure compliance with applicable laws and regulations. If you have questions, require accommodations, or wish to request human review were permitted by law, please contact your local HR representative. For more information, please visit NIQ’s AI Safety Policies and Guiding Principles: https://nielseniq.com/global/en/info/niqs-ai-safety-policies/ About NIQ NIQ is the world’s leading…

Responsibilities

• As a Senior Data Scientist, you will play a key role in developing end-to-end analytic solutions, shaping data and algorithms to deliver accurate and robust Predictive and Prescriptive Analytics.
• At NIQ, we’re looking for someone to join our Tech & Durable Global Data Science team, working at the intersection of business, data science and engineering to transform business problems into robust, production-ready Data Science solutions.
• Your Mission: Build scalable, production-ready data science solutions that enable the use of or directly utilize NIQ's Tech & Durable Point-of-Sale data.
• Collaborate cross-functionally with product managers, engineers, designers and business stakeholders to translate complex problems into actionable insights.
• Contribute to the evolution of our data science ecosystem through innovation, mentorship, and thought leadership.
• Responsibilities: Perform research to drive the development of product focused Data Science solutions for our T&D business.

Requirements / Eligibility

• nglish Desirable Skills: Familiarity with the evolving data science ecosystem and popular machine learning frameworks beyond PyTorch (e.g.
• Experience with software engineering best practices (version control, testing, agile development, Scrum, Safe).
• Hands-on experience with cloud computing platforms (e.g.
• GCP) and productionizing machine learning models (e.g.

How To Apply

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