Scalend is looking for a lead data scientist who will be responsible for developing predictive systems, creating efficient algorithms and improving data quality.

Key Responsibilities:

• Work with engineering on designing, building and deploying data analysis systems for large data sets

• Design, develop and implement prototype solutions and implementations using R & Python

• Create algorithms to extract information from large data sets

• Establish scalable, efficient, automated processes for model development, model validation, model implementation and large scale data analysis

• Develop metrics and prototypes that can be used to drive business decisions.

Minimum Requirements:

• Advanced degree in a relevant field such as Statistics, Computer Science or Applied Mathematics, or experience in the field

• Strong background in statistical concepts and calculations.

• 5+years experience with real data

• Extensive experience solving analytical problems using quantitative approaches

• Expert at data visualization and presentation.

• Experience with big data tools (e.g., Hadoop, HDFS, MongoDB, Hive, Storm)

• Excellent critical thinking skills, combined with the ability to present your beliefs clearly and compellingly verbally and in written form. 

Scalend is a high-growth startup - we do not offer fancy remuneration or perks. All we can promise is extraordinarily good learning, exposure to great customers, a fantastic environment, and excellent stock options.