Creation of predictive models for use cases across the company.
About The Job What You'll Do: Build predictive models, deploy them to production and monitor their performance Identify valuable data sources both from internal and external sources Undertake preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns Combine models through ensemble modeling Continuously challenge current models using new methods Propose solutions and strategies to business challenges What You Need To Have: BS/Master/PhD in Mathematics, Physics, Computer Science, Statistics, Engineering or similar numerate discipline 2-3 years of related work experience Willingness to learn and switch to Python which we use for majority of analytical projects Fundamentals of database management systems (Distributed computing, parallel processing, database modeling and design, relational databases, big data, Hadoop ecosystem (Hive, Impala, Spark), SQL language) Computer science fundamentals (Data structures, algorithms, computational complexity, object-oriented programming, knowledge of at least one programming language) Math and stats fundamentals (Numerical optimization, machine learning algorithms (neural networks, gradient boosting, regression), supervised and unsupervised learning, statistical inference, predictive modeling methodology and experiment design) Basics of business intelligence (Translating data into actionable insights, automation through data mart design, implementation and visualization of results (Tableau, Power BI)) What Can Set You Apart: Understanding of operations of a consumer finance/lending company Background in the following technologies: AWS Azure Spark/PySpark TensorFlow Job Perks You'll Enjoy: Hybrid work set up Permanent dayshift schedule Up to 20% variable performance-based bonus HMO on Day 1 and HMO dependents coverage including same-sex partners Access to mental health and wellness partners Wellness Leaves and Birthday Leave Internal career mobility options Local and international learning opportunities
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