ML Engineer (Research Scientist)

Key Skills

Python Programming, Scala Programming, C++, Java Programming, Machine learning techniques, Data science techniques, SQL, Apache Hadoop, MapReduce, TensorFlow, PyTorch, R Programming

Job Description

Our NielsenIQ Technology teams are working on our new Connected platform, a unified, global, open data ecosystem powered by Microsoft Azure. Our clients around the world rely on NielsenIQ data and insights to innovate and grow.

As a software engineer that wants to pursue a career in the field of Machine Learning operations (MLOps) you will be conducting technical reviews of scientific documentation with constructive criticism; understand and reproduce results from research experiments, conduct exploratory data analysis and design and develop scalable microservices to be deployed on-prem and on the cloud.

What you’ll do:

• Review and debug ML models along their life cycle; Collaborate with other teams to deploy ML models.

• Understand different business metrics and KPIs. Implement model monitoring strategies.

• Transform research models into actionable ideas and production services.

• Contribute to architectural designs of large complexity and size, potentially involving several distinct software components.

• Working closely with data scientists and a variety of end-users (across different cultures) to ensure technical compatibility.

• Work as a member of a team, encouraging team building, motivation and cultivating effective team relations.

• Support and maintain (troubleshoot issues with data and applications).

• Develop technical documentation for applications.

• Work on many different software challenges always ensuring a combination of simplicity and maintainability within the code.

We are looking for people with:

• Bachelor's degree in computer engineering.

• Experience in the use of collaborative developing tools such as Git, Confluence, etc.

• Minimal work experience of 3-4 years with evidence.

• Demonstrated experience and knowledge in Object-Oriented Programming.

• Proficiency in programming languages like Python.

• Problem-solving capabilities; Ability to learn quickly.

• Strong ability to analyze and synthesize (Good analytical and logical thinking capability).

• Ability to keep fluid communication written and oral in English, both written and spoken.

• Proactive attitude, resolutive, used to work in a team and manage deadlines.

•  Agile methodologies for software development.