Data Science Intern
at Lynx Analytics
Founded in 2010, Lynx Analytics is a predictive analytics company, with a team of world-class quantitative marketing scientists and industry-experienced data scientists. We openly welcome ideas and innovation, and believe in succeeding as a team – whilst having a great time doing it! By joining us, you’ll work with a collaborative group of diverse and talented individuals across our 10 global offices.
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. The internship period will be at least 3 months, taken place during the summer.
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:
- Implement (and partly design) solutions for a defined data science related problem under the guidance of lead / mid-senior data scientists
- Prepare presentations for the project stakeholders
- Create reusable documentations, presentations and code libraries during the projects
- Participate in internal education and research tasks
To succeed in this role, you should be currently pursuing an university degree in a technical field (Mathematics, Statistics, Economics, Computer Science or Engineering or related). You should also fulfill the following requirements:
- An interest in any of the following fields: finance, telecommunication, retail
- Understands complex algorithms
- Coding abilities at least one of the following languages: Python (preferred), R, SAS, C, JAVA (or similar). Software Engineer skills are not needed, but the candidate is expected to be able to write simple code to prototype and test analytical ideas. GitHub knowledge is a plus.
- Some data visualization skills/experience
- 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 the candidate is expected to be able to write simple code to prototype and test analytical ideas
- 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 in applied graph theory is a plus
- Knowledge of 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