Description

Being the Data Scientist, the right candidate will

• Mine, manipulate and perform statistical analysis on multiple data sets to build scalable enterprise analytics AI solutions
• Identify what data is available and relevant, including internal and external data sources and collaborates with institute subject matter experts to select the best approach
• Drive thought leadership in project and model approach from data acquisition to full production deployment
• Makes strategic recommendations on data collection, integration and retention requirements incorporating business requirements and knowledge of best practices
• Scope and define own work by researching and developing new content (Text & Computer Vision) that will drive large business impact opportunities
• Work with cross-functional business partners throughout the organization to identify opportunities for leveraging company data to drive business solutions
• Applies advanced statistical and predictive modeling techniques to build, maintain, and improve on multiple real-time decision systems
• Generate and validate hypotheses with variety of testing methods (A/B, multi-variate, factorial design) to measure the impact of ongoing campaigns and retail initiatives
• Communicate results and findings to key decision makers
• Lead corporate scale analytics projects that has a large impact on the organization
• Explore and research on best-in-class methodologies and latest technology trends
• Work with data engineers on the design and deployment of enhancements and fixes to systems as needed

Profile

• Bachelors / Masters Degree in relevant field (i.e. Mathematics, Statistics, Physics, Computer Science, Engineering, Econometrics)
• 3-5 Years working with big datasets and on large scale analytical projects
• In-depth knowledge on programming language such as R, Python or SAS to manipulate data and draw insights from large data sets
• Experience with data visualization tools/packs, such as D3.js, GGplot, Seaborn, Splunk, Power BI etc
• Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark,, MySQL, etc
• Must-have knowledge on a variety of machine learning techniques clustering, decision trees neural networks, Linear and Non-Linear Programming, Deep Learning (ANN, RNN, CNN) and their real-world advantages/drawbacks
• Experience analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Adwords, Facebook Insights, etc.
• Experience with merchandising and planning use cases is a plus
• Familiarity with AWS or Microsoft Azure or Google Cloud platform
• Nice to have: Working knowledge in NLP techniques such as topic modelling, named-entity recognition. semantic analysis, intent recognition etc.
• Nice to have: Working knowledge in image processing techniques such as image segmentation, Feature Matching, Image classification, Edge and Contour Detection techniques etc
• Willing to be proactive in coming up with solutions and accustomed to a collaborative start-up team environment
• Passionate about AI-related research and innovations
• Fluency in English is a plus
• Preferred background in retail, loyalty, ecommerce, merchandising or consulting