Offer summary

Qualifications:

B.Sc./M.A/M.Sc. degree in Computer Science, Engineering, Math, Statistics, or equivalent fields., 6+ years of experience as a Data Scientist with a strong background in machine learning concepts and models., Hands-on experience with Python and data science ML libraries, including regression and classification algorithms., Understanding of databases and SQL for data retrieval..

Key responsabilities:

Analyze large and complex data to discover hidden patterns and opportunities.

Develop and own end-to-end highly scalable data pipelines.

Collaborate with multiple teams to lead and accomplish overall solutions.

Oversee a complete release to production, including analyzing requirements and testing.

Job description

If you’re a talented Data Scientist looking to be part of a fast-growing innovative R&D team, shape the future of decision-making in business, work on cutting-edge technologies and vast amounts of global real-time data, affect billions of mobile users, and become an industry leader - then let’s talk! Our product is a mobile data platform that enables organizations to uncover insights and make data-driven decisions that enhance strategies and drive growth. We are seeking a Data Scientist to join our Data Science & Engineering team.

Requirements:

B.Sc./M.A/M.Sc. degree in Computer Science, Engineering, Math, Statistics, or other equivalent fields;
6+ years as a Data Scientist - a strong background in ML concepts and models;
Hands-on experience with Python, especially with data science ML libraries (regression & classification algorithms e.g. XGB or LGBM, recommendation system algorithms, etc.);
Understanding of databases and SQL for data retrieval;
Monitoring and alerting tools (e.g. Grafana, Kibana).

Advantage:

Experience in the AdTech industry;
Experience with relational (e.g. Vertica, VoltDB) and non-relational (e.g. MongoDB) databases;
Experience with PMML.

Responsibilities:

Analyze large and complex data to discover hidden patterns and opportunities;
Develop and own end-to-end highly scalable data pipelines;
Develop state-of-the-art machine learning models, and algorithms and build solutions in monetization fields;
Provisioning data models for real-time (online) processing;
Shape new data products, and constantly improve the existing products;
Collaborate with multiple teams including Product, BI, Analysts, DevOps, R&D, and Marketing to lead and accomplish overall solutions;
Oversee a complete release to production including analyzing requirements, testing, monitoring and measuring results, multitasking and quickly responding to critical issues.