Associate Data Scientist

Key Skills

Java Programming, Python Programming, SQL, Git, Scrum Agile Methodology, Machine learning techniques, Data science techniques, Data Mining, Deep Learning, Natural Language Processing (NLP), Data Analytics, Algorithms, Data Modelling, Data Classification, Text segmentation, Forecasting, Random forests, Decision Forests

Job Description

We’re looking for a passionate and talented Associate Data Scientist to join our growing team. In this role, you’ll have the chance to roll up your sleeves and apply data science methods and analytics to sustain NielsenIQ Analytics growth. Successful candidates are intellectually curious builders and active learners who are biased toward action, new problem solving.

Rationale

You’ve built a decent track record in research and data analytics. And you have the communication chops to translate it all into conversations. While you’ve worked with global cross-functional teams, you can also put your head down and focus on independent projects. Seeing the big picture takes attention to detail. Keeping up with the fast-changing world of technology takes someone who recognizes that. You know what’s happening in big data and you’re ready to influence what’s next.

Responsibilities :

• Understand business issues, stakeholder requirement and expectations
• Perform relevant modeling analysis and POC exploring multiple techniques
• Ensure Analytics model quality
• Document and present findings and recommendations on methodology in a structured way to various stakeholder or partnering teams (Engineering, Tech, Product leader).
• Work closely with the Engineering and Tech team to convert those POC into fully scalable products.
• Active and effective collaboration with other project team members (other Data Scientist, Data Steward, Technology Engineer)
• Stay abreast of developments in the area to ensure bringing the most appropriate solutions to our business

Qualifications

• Masters degree in Data Sciences, mathematics or a closely related field
• 1+ years of experience as a Data Scientist in the business
• Strong theoretical knowledge of statistical modelling and foundational mathematical concepts.
• Experience in machine learning, supervised and unsupervised: Forecasting, Classification, Data/Text Mining, NLP, Decision Trees, Adaptive Decision Algorithms, Random Forest, Search Algorithms, Neural Networks, Deep Learning Algorithms
• Experience with Optimization techniques: linear programming, integer programming, genetic algorithm, constrained optimization
• Experience in working on distributed or cloud computing platforms such as Google Cloud or Microsoft Azure
• Proficiency in Data Science coding languages like Python
• Proficiency in SQL
• Experience using collaborative development tools (git).
• Experience working with Agile methodologies (SCRUM)
• Strong problem solving and excellent communication skills, independent working style

Additional Information

All your information will be kept confidential according to EEO guidelines.

About NielsenIQ 

NielsenIQ is a global measurement and data analytics company that provides the most complete and trusted view available of consumers and markets worldwide. We provide consumer packaged goods manufacturers/fast-moving consumer goods and retailers with accurate, actionable information and insights and a complete picture of the complex and changing marketplace that companies need to innovate and grow. Our approach marries proprietary NielsenIQ data with other data sources to help clients around the world understand what’s happening now, what’s happening next, and how to best act on this knowledge. We like to be in the middle of the action. That’s why you can find us at work in over 90 countries, covering more than 90% of the world’s population. For more information, visit .

NielsenIQ is committed to hiring and retaining a diverse workforce. 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.