Data Science Intern (Jan to Jun)

Key Skills

Python Programming, SQL, Apache Hive, Teradata, R Programming, MySQL, Statistics, PySpark, SPARK Programming

Job Description

Founded in 2010, Lynx Analytics is a predictive analytics company run by world-class quantitative marketing scientists and industry-experienced data scientists. Our focus is to become the world’s leading telecom analytics solution provider, whilst advancing graph analytics technology.

We are looking for Data Science 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.

You 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 modelling and optimization techniques most suited for the business problem (using R, Python, SQL, and/or other relevant tools)
• Implement (and partly design) solutions for a defined data science related problem under the guidance of lead / mid-senior data scientists
• 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 modelling 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

We’re looking for:

• Full-time interns (at least 6 months)
• An interest in any of the following fields: finance, telecommunication, retail
• Currently in the final year of university studies in the field of Mathematics, Statistics, Economics, Computer Science, Engineering or related 
• Understands complex algorithms
• Ability to write programs in some programming language (e.g. R/Python) to prototype and test analytical ideas
• Some data visualization skills/experience
• Strong probability theory and statistics knowledge and some of the main data science algorithms. 
• Knowledge of their application in Customer Retention, Campaign Management etc. areas is an advantage
• Good problem-solving skills
• Excellent verbal and written communication skills
• Knowledge of applied graph theory or any DWH querying languages (like SQL, hive, Teradata, MySQL etc.) or Spark / pySpark is an advantage
• Participation in Kaggle challenges, presentation in meetups, having a DS related blog / own GitHub page or doing charity DS activities is a plus
• Fluency in English