ML Engineer

As an ML Engineer at NielsenIQ, you will play a crucial role in transforming experimental marketing science prototypes into scalable, production-ready solutions within the Marketing Effectiveness Incubation Lab. Your work will be fundamental in ensuring the quality, performance, and reproducibility of next-gen ideas that graduate from proof-of-concept to NIQ's evolving marketing analytics platform. You will be part of a culture that values innovation, client-centricity, and engineering rigor. Key Responsibilities: - Develop, implement, and standardize marketing science solutions originated within the Lab, turning proofs-of-concept into scalable, reusable, production-ready code. - Build analytical pipelines at scale using cloud services, containerized applications, and distributed systems to support pilot deployments and graduation hand-offs. - Optimize Lab models and algorithms through code optimization, high-performance computing, and real-time techniques. - Continuously enhance the efficiency and quality of Lab solutions, ensuring adherence to coding guidelines, testing standards, documentation, and reproducibility. - Identify best practices and contribute to the improvement of tooling, infrastructure, and engineering methods within the Lab. - Collaborate closely with Senior Data Scientists and the Incubation Labs Product Lead to translate experimental code into platform-ready components. - Partner with downstream Product & Tech teams to facilitate the smooth transition of Lab innovations into the broader marketing analytics platform. - Act as a key engineering support resource for issues, bugs, and blockers on Lab-deployed models and pipelines. - Stay updated with advancements in software engineering, ML infrastructure, MLOps, and AI tooling to apply them effectively within the platform. Qualifications: - Bachelors or Masters degree reflecting strong statistical, mathematical, or computer science skills. - 3+ years of professional Python development experience. - Working understanding of R. - Experience with statistical and predictive modeling. - Proficiency in managing code deployments with strong Git experience. - Solid grasp of containerization (Docker), building and managing images. - Familiarity with cloud platforms (AWS, Azure, or GCP) and distributed systems. - Experience in creating, managing, and maintaining code documentation. - Ability to present and explain technical concepts to both technical and non-technical stakeholders effectively. In addition to the job details, NielsenIQ promotes a culture of diversity, equity, and inclusion in the workplace. They value individuals who share their dedication to inclusivity and equity and invite them to be part of the team to make a meaningful impact. As an ML Engineer at NielsenIQ, you will play a crucial role in transforming experimental marketing science prototypes into scalable, production-ready solutions within the Marketing Effectiveness Incubation Lab. Your work will be fundamental in ensuring the quality, performance, and reproducibility of next-gen ideas that graduate from proof-of-concept to NIQ's evolving marketing analytics platform. You will be part of a culture that values innovation, client-centricity, and engineering rigor. Key Responsibilities: - Develop, implement, and standardize marketing science solutions originated within the Lab, turning proofs-of-concept into scalable, reusable, production-ready code. - Build analytical pipelines at scale using cloud services, containerized applications, and distributed systems to support pilot deployments and graduation hand-offs. - Optimize Lab models and algorithms through code optimization, high-performance computing, and real-time techniques. - Continuously enhance the efficiency and quality of Lab solutions, ensuring adherence to coding guidelines, testing standards, documentation, and reproducibility. - Identify best practices and contribute to the improvement of tooling, infrastructure, and engineering methods within the Lab. - Collaborate closely with Senior Data Scientists and the Incubation Labs Product Lead to translate experimental code into platform-ready components. - Partner with downstream Product & Tech teams to facilitate the smooth transition of Lab innovations into the broader marketing analytics platform. - Act as a key engineering support resource for issues, bugs, and blockers on Lab-deployed models and pipelines. - Stay updated with advancements in software engineering, ML infrastructure, MLOps, and AI tooling to apply them effectively within the platform. Qualifications: - Bachelors or Masters degree reflecting strong statistical, mathematical, or computer science skills. - 3+ years of professional Python development experience. - Working understanding of R. - Experience with statistical and predictive modeling. - Proficiency in managing code deployments with strong Git experience. - Solid grasp of containerization (Docker), building and managi