Data Analyst (Python, R) at NielsenIQ

Vadodara, gujarat, India -

Full Time

Start Date

Immediate

Expiry Date

23 Jun, 26

Salary

0.0

Posted On

25 Mar, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, R, Data Analysis, Machine Learning Model Monitoring, KPI Dashboards, Feedback Loop Establishment, Model Tuning, Model Optimization, Anomaly Detection, NumPy, Pandas, Matplotlib, Communication, Analytical Mindset, Stakeholder Management

Industry

Software Development

Description

Job Description Grade level: T4 Superior’s Position: RD GOT Innovation Leader (Business Process Architect) As a member of the Innovation team, you will work in a dynamic, multinational, and virtual environment collaborating with colleagues across Data Ops and Global Operations Transformation teams globally. Purpose of the job: Data Analyst/Engineer oversees the optimal performance of machine learning (ML) models within their life cycle. 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: RESPONSIBILITIES: Continuous Monitoring: 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 using existing KPI dashboards. Data Analysis: They analyze large volumes of raw data generated by ML models (prediction and feedback), identifying patterns, trends, and anomalies. This analysis helps in understanding the behavior of models under different conditions and detecting any potential issues. The final goal of their job is to identify a root cause that led to a drop in the data trend. 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. Data analysts provide timely feedback to ML engineers 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, ML research and MLOps 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. 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 ML engineers, developers, and operations teams. Effective communication and collaboration are essential to implementing improvements seamlessly. Qualifications Work Experience: Proven 1-2 years track record in a related field (KPIs monitoring, big data analysis, ML models development) with hands-on experience within data analytics. Requirements: Solid skills in Python, including analytical libraries (NumPy, Pandas, Matplotlib, etc.) Hands-on experience within data analytics Solid communication skills in English in writing and speaking An analytical mindset (candidates will complete a case study) Experience in owning tasks, driving progress and working out solutions Readiness to cover an ‘extra mile’ while executing tasks Willingness to learn and grow Ability to work and build relationships with stakeholders at various levels of organization is a plus. Experience of software development is a plus. Education: Bachelor’s degree (Science, Technology, Math or Engineering background) Additional Information 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://www.nielseniq.com/global/en/ai-safety-policies. 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 Want to keep up with our latest updates? Follow us on: LinkedIn | Instagram | Twitter | Facebook Our commitment to Diversity, Equity, and Inclusion At NIQ, we are steadfast in our commitment to fostering an inclusive workplace that mirrors the rich diversity of the communities and markets we serve. We believe that embracing a wide range of perspectives drives innovation and excellence. All employment decisions at NIQ are made without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other characteristic protected by applicable laws. We invite individuals who share our dedication to inclusivity and equity to join us in making a meaningful impact. To learn more about our ongoing efforts in diversity and inclusion, please visit the https://nielseniq.com/global/en/news-center/diversity-inclusion Career Site Team: Operations

Responsibilities

The Data Analyst/Engineer oversees the optimal performance of machine learning (ML) models throughout their lifecycle, primarily through continuous monitoring and analysis of key metrics like accuracy and precision. A critical part of the role involves establishing feedback loops, providing timely input to engineers, and collaborating on model tuning and optimization based on identified patterns and anomalies.