– Strong knowledge in computer science fundamentals, algorithms, mathematics, linear algebra, graph theory, probability and statistics.
– Hands-on experience in handling diverse data sets with strong analytics concepts and ML libraries. Also, working knowledge of spark, kafka, hadoop.
– Proficient in python and using libraries — nltk, sklearn, numpy, scipy, pandas, pymongo, sqlalchemy
– Comfortable with flask framework.
– Comfortable with web scraping, extracting, manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources.
– Strong passion for data-driven research for answering hard questions with data.
– Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner.
– Having a good understanding of design principles.
– Passionate about startups and the ability to work in a fast-paced environment.
Problems you will be working on:
– Build analytics to measure the quality of results from user interaction data.
– Conceptualize and develop novel techniques to understand food data and improve the personalization algorithm.
– A/B test various techniques/tunings to personalization models.
– Introduce self-learning models based on various data points to improve the accuracy of prediction.