Lynx Analytics – Data Scientist Intern

We are looking for 3 Data Scientist Interns to support our Data Science team in complex data analysis projects using standard modelling and data transformation approaches as well as Lynx's proprietary graph analysis system. The internship period will be at least 3 months, up to 6 months.
The candidate should be comfortable working with very large data sets residing in different data stores in disparate formats and be strong with hands-on implementation, as well as have the potential to move fast onto a high growth career trajectory.

Key Responsibilities Will Include

• Conduct quantitative and qualitative analysis, including obtaining the data, cleaning it and exploring it for accuracy
• Deploy statistical modeling and optimization techniques most suited for the business problem (using R, Python, SQL, and/or other relevant tools)
• Help the Data Science Team on analytic methodologies and approaches to address the clients' specific needs, including discussing data collection, architecture, associated costs and trade-offs, and recommendations
• Interpret outputs of statistical models and results to translate input from quantitative analyses into specific and actionable business recommendations and implications
• Providing detailed documentation of modeling techniques, methodologies, assumptions made and process steps
• Manage delivery of analytical solutions via written and verbal presentations
• Provide research on topics
• Identify areas for further investigation as well as creating innovative methods of analysis

To succeed in this role, you should be currently pursuing a University degree in a technical field (Mathematics, Statistics, Economics, Computer Science or Engineering). You should have strong probability theory and statistics knowledge, knowledge of some statistical tools and knowledge of RDBMS systems (Oracle, Teradata, MySQL etc.). You need to have good problem-solving skills and some data visualization skills/experience. In addition, the ability to write programs in some programming language (e.g. R/Python) - software engineering skills to design and implement complex software systems is not needed, but you are expected to be able to write simple code to prototype and test analytical ideas.