Curve’s predictive modelling platform enables retailers and e-merchants to
reduce costs, identify growth opportunities, and generate personalized
customer experience by using machine learning algorithms. Curve transforms
unstructured historical data into meaningful information and actionable
insights that positively drives business productivity and bottom-lines.
About the Role:
We are looking for a Data Scientist to join our data team. As a data scientist
in curve you will take part in our ongoing endeavour of developing a robust
analytic pipeline that is able to digest multiple types and forms of data
without manual intervention and use advanced analytics to supply predictive
insight. We work with many types of data and with every processing and
modelling technique out there.
Our data team consists of skilled and experienced professionals with both
academic and industry background in multiple scientific fields and we are
seeking someone creative, smart and fun to work with to complement our
versatile team.
In order to excel in our team, you need to be a skilled data scientist and a
strong python developer.
Primary Responsibilities:
• Design, implement and deploy ML/DL algorithms
• Apply quantitative analysis and an insightful presentation of data to see
beyond the numbers and understand how our users interact with our growth
products
• Automate data collection procedures, and pre-processing of structured and
unstructured data
• Analyse large amounts of data to discover trends and patterns
• Apply data mining techniques, perform statistical analysis, and build high-
quality prediction modelling
• Meet the business vision and strategy in accordance with the product
innovation backlog
• Collaborate with the product, engineering, and UX/UI teams to deliver usable
and informative analytical interfaces
Basic Requirements:
• 2+ Years of proven experience as a Data Scientist, preferably working with
B2C / B2B2C
SaaS products
• Python expert!
• Excellent understanding of machine learning techniques and algorithms and
methodology
• Experience with common data science toolkits, such as Pandas, Scikit-learn,
Tensorflow, FeatureTools and more
• High-level applied statistics skills, such as distributions, statistical
testing, etc.
• Experience in data mining and insight drawing from large data sets
• Proficiency in using query languages such as SQL, Hive, Pig
• Data-oriented personality, analytical mind, and problem-solving aptitude
• Team player with excellent communication and presentation skills to tech /
non-tech people alike
• in Computer Science, Engineering, Mathematics or relevant field; graduate
degree in Data Science or other quantitative field is preferred
Fluent in English, both written and verbal
