Data Scientist

About the job

Responsibilities include collaboration with clients and internal project teams to analyze and develop algorithms for solving real-life operational challenges through purpose-built software and machine automation. This position will be a mix between pre-processing database engineering, critical thinking from a data science point of view, data visualization and business intelligence.

Data Scientist candidate should possess the following:

• Degree in statistics, mathematics, operations research, economics or other quantitative field

• Strong analytical aptitude and an understanding of statistical methods

• Excellent problem solving skills

• Excellent oral and written communication skills

• Experience of relational databases (SQL) and ETL data processing with thorough understanding of data structures, algorithms and design best practices

• Experience working with distributed computing tools like Hadoop is a plus

• Strong background in statistics and machine learning (clustering, classification, and regression)

• Experience in Data analysis tools (e.g., Matlab, R, Excel, SQL)

• At least 5 year of Object-Oriented Programming with languages such as Python, C, C++ or Java a requirement.

• At least 1 year of experience working with visualization software/tools like Tableau, QlikView, or Pentaho preferred

• At least 1 year of experience with prototyping/mock-ups/storyboards is a plus

• An understanding of UI/UX design concepts is a plus

The Data Scientist candidate will perform the following tasks:

• Data integrations, ETLs and use of API to pull and push data from multiple data sources

• Track down complex data and engineering issues, evaluate different machine-learning algorithmic approaches, and analyze data to solve problems

• Build mathematical models on top of client data to gain business insight into opportunities to improve the customer’s operation

• Write programs/scripts to analyze data, working in Python

• Participate in discussions with business users to understand scorecard requirements and propose suitable visualizations options (mock-ups) depending on the need, context and user group

• Design visual representations of the data set(s) and iterate with client to finalize design

• Conduct and communicate complex analyses in a clear and actionable manner to non-experts

• Facilitate development of common visualization objects that can be shared across multiple visualizations to drive development efficiency and user experience consistency

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