Position: Data Scientist
Company: GeoZilla
Category: Data Science
Experience required: 3y
English level: intermediate

We are looking for a talented data scientist with strong engineering background to kick start an exciting new direction in our well established consumer app business.
You will be responsible for designing and building ML based solution which predict safety hazards before they happen, and work on improving our product quality by optimising the accuracy of our location data.

Requirements:
— Bachelor’s degree in statistics, applied mathematics, or related discipline;
— 4+ years experience in data science;
— Proficiency with data mining, mathematics, and statistical analysis;
— Advanced pattern recognition and predictive modeling experience;
— Excellent analytical and problemsolving skills;
— Experience in database interrogation and analysis tools, such asZeppelin, Anaconda, Pandas, ScikitLearn, Jupyter, SQL, Spark;
— Experience in programming languages and Python, Scala;
— Communication and presentation skills in order to explain your work to people who don’t understand the mechanics behind data analysis;
— Effective listening skills in order to understand the requirements of the business;
— Drive and the resilience to try new ideas if the first one doesn’t work you’ll be expected to work with minimal supervision, so it’s important that you’re able to motivate yourself;
— Planning, time management and organisational skills;
— Great attention to detail;
— Teamworking skills and a collaborative approach to sharing ideas and finding solutions.

Обязанности
— Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions;
— Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies;
— Assess the effectiveness and accuracy of data sources and data gathering techniques;
— Develop custom data models and algorithms to apply to data sets;
— Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business out comes;
— Develop company A/B testing framework and test model quality;
— Coordinate with different functional teams to implement models and monitor outcomes;
— Develop processes and tools to monitor and analyse model performance and data accuracy.