Lead Data Scientist Job Description Template
Our company is looking for a Lead Data Scientist to join our team.
Responsibilities:
- Mentor and lead a small team;
- Create advanced data science applications to be productionised and used throughout the business;
- Engage with business stakeholders (including non-technical individuals);
- Build a variety of recommender systems using reinforced learning;
- The successful candidate will be able to communicate with different stakeholders at different organizational levels;
- Responsible for delivering regular, timely and actionable data insight and providing detailed analysis;
- Solve business problems, determining patterns and insights within structured and unstructured data, coming up with analytics strategies and solutions;
- Applying machine learning strategy to provide insights;
- Providing input to carry out the Data Science needs within the company;
- Providing commercially viable applications using deep learning techniques;
- Deploy, implement and maintain Machine Learning models;
- Perform duties such as collecting, parsing, tagging, analyzing, mapping, managing, and visualizing large sets of data;
- You will be given the autonomy to develop new ideas from scratch, utilising previous data development experience to add vale to the analytics team;
- Experiment, train and deploy machine learning models at scale.
Requirements:
- Python or R;
- FS/Banking background highly desirable;
- Understanding and experience of modelling techniques;
- Use Deep Learning frameworks;
- Understanding customers needs through AI;
- Creating models to analyse interactions;
- Good understanding of probability and hypothesis testing;
- Be an expert in programming with SQL and Python or R with an extensive history of doing so in previous roles;
- Very comfortable with the fundamentals of a wide range of machine learning techniques;
- Highly skilled programming expertise in Python and/or R;
- SME around statistical modelling & machine learning learning techniques;
- Strong knowledge of programming methodologies (Python or R);
- Quantitative background: machine learning, data analysis, optimization, statistics;
- Good working knowledge of programming in Python and/or R and the ability to write readable, efficient code;
- MSc or PhD degree in a quantitative discipline such as Maths, Data Science, Engineering, Computer Science, or similar.