What are the responsibilities and job description for the Data Scientist position at Hellman & Friedman?
Company Description
The world around us is changing. Retail is in a state of major transition, and consumers have more options than ever. As a leading provider of global information and advisory services, NPD is at the forefront of helping our clients, the world's biggest brands and retailers understand and profit from these changes.
Since 1966, we have been helping businesses track industry trends and understand their customers in order to get the right products in the right places for the right people at the right prices. We serve more than a dozen industries including consumer electronics, entertainment, fashion, food / foodservice, toys, video games, and more.
We want to lead manufacturers and retailers on collaborating via the effective use of our information in line reviews and joint business planning.
Job Description
NPD group is looking for a principal data scientist on both the engineering side and the analytics side of data science. This position resides in the Global Data Quality Management group. He or she will combine the skills to create new prototypes with the creativity and thoroughness to interrogate the most challenging questions about data quality, which is at the center of NPD's value creation for our clients. This is a leadership position and will require superior ability to quickly gather information and requirements from stakeholders, formulate solution, and implement the solution within the data quality groups. This position will interact frequently with senior leadership teams and will direct and manage the work of junior data scientists. Qualified candidates will have a strong academic background in mathematics, statistics, computer science, operational research, economics, and other highly quantitative disciplines, passion about data science and machine learning and experience with big data architecture and methods.
Overall Responsibilities :
- Drive the creation of new data quality management capabilities that will bring significant operational efficiency.
- Conceptualize, analyze and develop actionable recommendations best practices in data quality processes
- Work with key stakeholders and understand their needs to develop new or improve existing solutions around data quality.
- Manage data analysis to develop fact-based recommendations for innovation projects.
- Work with cross-functional teams to develop ideas and execute business plans.
- Remain current on new developments in data quality
Qualifications
Additional Information
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