Sr. Data Scientist
Location: Remote USA
Job Type: Data Science
IQ Workforce is a leading recruiting firm for the engineering, analytics, and data science communities.
Our client is a global restaurant company, which engages in the development and operation of some of the most recognizable brands in the world. They have over 30,000 employees and operate over 50,000 restaurants in 150+ nations and territories.
They are currently looking to add another Sr. Data Scientist to add to their dynamic and rapidly scaling Data Science team. They are making this investment to help optimize their digital channels and technology innovations, with the end goal of creating competitive advantages for their restaurants around the globe.
They are seeking a candidate who has practical experience with technologies and languages supporting big data and data science domains. The Sr. Data Scientist will develop and maintain statistical models, apply machine learning techniques and build high-quality predictive/prescriptive systems. They also make technology and business recommendations, as well as develop key insights based on data analysis in both macro- and micro-environments. This person must be able to partner with key stakeholders in their business to completely understand context and guide which business priorities they should address using data … and how they should go about doing so. Overall, the Sr. Data Scientist will serve as a domain expert and will develop a rapport with their internal business partners as an essential, long-term part of the team.
Partner with internal restaurant brands to identify opportunities to leverage company data to drive business outcomes
Play key role in our advance analytics team developing data science solutions, responsible for driving company growth
Build predictive models to elevate the customer experience and drive revenue growth in our restaurants globally
Implement globally scalable, cross brand solutions related to data science
Deliver solutions leveraging the latest machine learning (ML) techniques, including exploratory data analysis; feature engineering; model selection; model evaluation and cross-validation; and deployment and productionalization at all scales.
Collaborate with our Yum! data science teams to enhance, scale and operationalize existing models.
Communicate effectively with both technical and nontechnical stakeholders.
Provide thought leadership on latest ML and artificial intelligence (AI) technologies and applications for our company use cases.
Conduct and support white-boarding sessions, workshops, design sessions and project meetings as needed, playing a key role in cross-functional business relations.
Develop data science solutions as currently defined by the existing product roadmap.
Prototype algorithms using Python and/or other languages with appropriate libraries and frameworks.
Master’s degree/Ph.D. in a quantitative field (statistics, mathematics, business analytics, computer science or business administration) with a specific emphasis on statistics, (big) data mining and data science, etc.
5+ years of experience in data science.
Advanced analytical and quantitative skills to use data and metrics to back up assumptions, evaluate the hypothesis and complete root cause analysis of the business problem.
Deep understanding of supervised and unsupervised machine learning techniques.
Hands-on experience working with regression, clustering, support vector machines, neural networks (including CNN and RNN), decision trees and related models.
Experience working with natural language processing (NLP) models.
Knowledge of the full data mining steps from data preparation, modeling, visualization and interpretation.
In-depth knowledge of Python, R, SQL and any analytics platforms (such as Alteryx, KNIME, RapidMiner and Data Robot, etc.) is strongly desired.
Experience in integrating business analysis with technical solutions that involve advanced analytics solutions, demand forecasting, segmentation, churn prediction, predictive maintenance and route optimization, etc.
Ability to work with key business stakeholders throughout the organization to identify opportunities for leveraging our data to drive business solutions by using advanced analytical methods.