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Job Description

This data Analyst/Engineer oversees the optimal performance of machine learning (ML) models within a DevOps environment. Their primary responsibilities involve continuous monitoring, analysis, and feedback provision to enhance the overall efficiency of ML models. Here's a summarized breakdown of their role: 


  • Continuous Monitoring: DevOps data analysts constantly monitor the performance of ML models in real-time. This involves tracking key metrics such as accuracy, precision, recall, and other relevant indicators. 
  • Data Analysis: They analyze large volumes of data generated by ML models, identifying patterns, trends, and anomalies. This analysis helps in understanding the behavior of models under different conditions and detecting any potential issues. Model and data to be analyzed for Data drift and Model drift to assist future actions. 
  • Feedback Loop: Establishing a feedback loop is a critical aspect of their role. Monitoring the feedback of results resulted from each model on each iteration.  DevOps data analysts provide timely feedback to data scientists and developers about the model's performance, suggesting improvements or adjustments to enhance accuracy and efficiency. 
  • Model Tuning and Optimization: Based on their analysis, they collaborate with the development and data science teams to fine-tune and optimize ML models.  This may involve adjusting hyperparameters, incorporating new data, or retraining models to improve overall performance. 
  • Anomaly Detection: Identifying and addressing anomalies in model behavior is a key responsibility. DevOps data analysts work to detect issues such as drift in data distribution, unexpected bias, or performance degradation, taking corrective actions when necessary. 
  • Collaboration with Cross-functional Teams: They work closely with various teams involved in the ML development lifecycle, including data scientists, developers, and operations teams. Effective communication and collaboration are essential to implementing improvements seamlessly. 

In summary, the role involves continuous monitoring, analysis, and feedback provision to ensure the optimal performance of ML models. This collaborative and proactive approach contributes to the overall success of the DevOps pipeline in deploying and maintaining robust machine learning applications. 


Junior Software Engineer / Data Analyst / Support software Engineer/ 


Responsibilities 


  • Monitor and support Data Scientist and Engineers to collect data points which help to optimize performance of machine learning models, identifying anomalies and implementing proactive measures.  
  • Data science models testing, validation and tests automation 
  • Communicate with a team of data scientists, data engineers and architect, document the processes  
  • Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc. 
  • Support to improve performance, maintainability, and reliability of our clients’ machine learning systems 

Qualifications 


  • Bachelor’s degree in Computer Applications or Computer Science or Software Engineering 
  • Software engineering skills  
  • Knows Python and good to have with ML background 
  • Knows Linux and server knowledge 
  • Good to have database systems knowledge 
  • Good to have monitoring and maintaining ML systems built with open source tools 
  • Good to have understanding in software testing, benchmarking, and continuous integration 
  • Eager to learn machine learning methodology 
  • Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc.) 

Education & Experience 


  • 1–3 years experience building production-quality software. 
  • Bachelors or Masters degree and/or equivalent professional experience 

Additional Information

Our Benefits


  • Flexible working environment
  • Volunteer time off
  • LinkedIn Learning
  • Employee-Assistance-Program (EAP)

About NIQ


NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population.


For more information, visit NIQ.com


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Our commitment to Diversity, Equity, and Inclusion


NIQ is committed to reflecting the diversity of the clients, communities, and markets we measure within our own workforce. We exist to count everyone and are on a mission to systematically embed inclusion and diversity into all aspects of our workforce, measurement, and products. We enthusiastically invite candidates who share that mission to join us. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability status, age, marital status, protected veteran status or any other protected class. Our global non-discrimination policy covers these protected classes in every market in which we do business worldwide. Learn more about how we are driving diversity and inclusion in everything we do by visiting the NIQ News Center: https://nielseniq.com/global/en/news-center/diversity-inclusion




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