ABOUT THE ROLE
The purpose of our Data Scientist role is to answer complex analytical questions from big data sets to help us shape and deliver even better products and services.
• Design and develop statistical & machine learning models to support Mondia Group decisions.
• Identify and discover hidden patterns in complex structured and unstructured data sets.
• Enable look a-like modelling, propensity to churn, propensity to buy, CLV, clustering, collaborative filtering, RFM, Marketing-mix, predictive modelling and audience profiling.
• Champion metrics creation, manipulate, transform and verify quality of data.
• Work with data engineering team to implement Big data analytics roadmap.
• Work with data governance team to help drive consistency in MDM and data definitions to create a trusted source of data.
• Make recommendations for data harmonization and customer centricity.
• Develop an acute understanding of product, marketing and business needs through constant engagement with internal and external stakeholders.
• Strong problem solving and decision-making skills.
The ideal candidate will have exceptional communication skills with the ability to effectively articulate and recommend innovative data solutions, breaking down complex information into understandable and actionable items. You will be self-driven and able to work independently. Those with experience in the technology industry would be at a distinct advantage.
Other qualifications include:
• Minimum 5 years experience in solving analytical problems through data driven quantitative methodologies and creating econometric descriptive and predictive models in Digital space. (unstructured data)
• BS in Mathematics, Economics, Computer Science, Information Management or Statistics
• Experience with Amazon Web Services Big data platform (ie. S3, RS) or any other Cloud Datawarehouse
• Solid experience with digital measurement and analytics platforms (ie. Google analytics, Big query, Return path data)
• Strong knowledge and experience in data modelling and wrangling techniques
• Strong knowledge and experience using Big Data programming languages (mainly R and Python)
• Strong knowledge of machine learning algorithms like Random Forrest, Decision trees, Matrix forecasting, Time series, Bayesian networks, Clustering, Regression and classification
• Experienced in using SPARK, HIVE, SQL. NoSQL, Big query, Hadoop, HDFS, Hive, Lambda, Kinesis
• Knowledge and experience in Data Visualization
• Understanding of standard digital technologies used for commercial VOD, ecommerce and subscription services including cookies, working with tag management data and data layers or SDKs and ad-serving technologies
• Ability to communicate highly complex concepts in layman language