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.
5years 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.