Postings
Browse:

Volunteer Opportunity

Analyst, Business Intelligence

NielsenIQ India

Deadline: Not specified

Short Summary

Analyst, Business Intelligence with NielsenIQ. Job Summary We are seeking a highly skilled Python & Generative AI Engineer (6–8 years experience) to design, build, and optimize scalable, cloud-native AI applications. This role blends hands-on development, system design, and applied AI engineering, with a focus on Large Language Models (LLMs) and Small Language Models (SLMs). The ideal candidate is a strong backend engineer…

Key Details

  • Position / opportunity: Analyst, Business Intelligence
  • Organization: NielsenIQ
  • Country / coverage: India
  • Location: Chennai, TN, India
  • Work arrangement: On-site
  • Opportunity type: Volunteer opportunities
  • Sector: Education
  • Compensation: Not specified
  • Duration: Not specified
  • Start date: 2026-08-24
  • Application deadline: Not specified

Description

Job Summary We are seeking a highly skilled Python & Generative AI Engineer (6–8 years experience) to design, build, and optimize scalable, cloud-native AI applications. This role blends hands-on development, system design, and applied AI engineering, with a focus on Large Language Models (LLMs) and Small Language Models (SLMs). The ideal candidate is a strong backend engineer with experience in distributed systems and AI-driven applications, capable of owning features end-to-end while contributing to architecture, performance optimization, and model fine-tuning workflows. Key Responsibilities Design and develop scalable, cloud-native applications using Python Build and maintain APIs and backend services with a strong focus on performance, reliability, and maintainability. Performed automated data validation, missing value detection, duplicate analysis, and anomaly detection using Pandas and Polars. Developed business rule engines to identify KPI deviations, performance gaps, and data quality issues. Integrated Large Language Models (Azure OpenAI/Llama) to generate executive summaries, business insights, and recommendations. Develop and integrate Generative AI solutions, including LLM-based applications and prompt engineering techniques. Contribute to the design of distributed and event-driven systems with high availability. Collaborate with architects and senior engineers to implement scalable and extensible system designs. Implement CI/CD pipelines, automated testing, and DevOps best practices. Leverage AI-assisted development tools (e.g., GitHub Copilot) to improve development efficiency. Ensure code quality through testing, reviews, and adherence to engineering standards. Monitor and optimize applications using logging, monitoring, and observability tools. Work closely with cross-functional teams to deliver AI-powered business solutions. SLM fine-tuning for edge or cost-efficient deployments Bachelor's degree in computer science, Engineering, or a related field. 6–8 years of experience in software development. Must-Have Skills Strong proficiency in Python and object-oriented programming. Experience with SLM deployment on edge or low-latency environments. RAG (Retrieval-Augmented Generation), or vector databases. Hands-on experience with Generative AI / SLMs and prompt engineering. Solid understanding of data structures, algorithms, and design patterns. Experience with cloud platforms (Azure, AWS, or GCP). Experience with CI/CD pipelines, version control (Git), and DevOps practices. Knowledge of distributed systems fundamentals and microservices architecture. Experience with testing frameworks such as Pytest. Strong debugging, problem-solving, and analytical skills. Leveraged Azure OpenAI, LangChain, and vector search to build enterprise-grade GenAI applications. Good-to-Have Skills Familiarity with Infrastructure as Code (Terraform, Pulumi). Experience with LLM fine-tuning Experience with SLM deployment on edge or low-latency environments Experience with observability tools (Prometheus, Grafana, OpenTelemetry, etc.). Knowledge of polyglot persistence (SQL & NoSQL databases). Familiarity with AI-assisted coding tools like GitHub Copilot. Exposure to containerization and orchestration (Docker, Kubernetes). Prior experience working in Agile/Scrum environments. 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…

Responsibilities

  • Job Summary We are seeking a highly skilled Python & Generative AI Engineer (6–8 years experience) to design, build, and optimize scalable, cloud-native AI applications.
  • This role blends hands-on development, system design, and applied AI engineering, with a focus on Large Language Models (LLMs) and Small Language Models (SLMs).
  • The ideal candidate is a strong backend engineer with experience in distributed systems and AI-driven applications, capable of owning features end-to-end while contributing to architecture, performance optimization, and model fine-tuning workflows.
  • Key Responsibilities Design and develop scalable, cloud-native applications using Python Build and maintain APIs and backend services with a strong focus on performance, reliability, and maintainability.
  • Performed automated data validation, missing value detection, duplicate analysis, and anomaly detection using Pandas and Polars.
  • Developed business rule engines to identify KPI deviations, performance gaps, and data quality issues.

Requirements / Eligibility

  • Experience with cloud platforms (Azure, AWS, or GCP).
  • Experience with CI/CD pipelines, version control (Git), and DevOps practices.
  • Knowledge of distributed systems fundamentals and microservices architecture.
  • Experience with testing frameworks such as Pytest.

How To Apply

Use the Apply now button and follow the instructions on the application page.