Your colleagues
Work with other data scientists, data engineers, machine learning engineers, designers and project managers on interdisciplinary projects, using maths, stats and machine learning to derive structure and knowledge from raw data across various industry sectors.
Who You Are
You are a highly collaborative individual who is capable of laying aside your own agenda, listening to and learning from colleagues, challenging thoughtfully and prioritising impact. You search for ways to improve things and work collaboratively with colleagues. You believe in iterative change, experimenting with new approaches, learning and improving to move forward quickly.
Our Tech Stack
While we advocate for using the right tech for the right task, we often leverage the following technologies Python, PySpark, TensorFlow, PyTorch, SQL, Airflow, Databricks, our own OSS called Kedro (check out a Kedro tutorial video here), container technologies such as Docker and Kubernetes, cloud solutions such as AWS, GCP or Azure, and more!
What You'll Do
As a data scientist at QuantumBlack, you will work in multi-disciplinary environments harnessing data to provide real-world impact for organisations globally. You will influence many of the recommendations our clients need to positively change their businesses and enhance performance.
Role Responsibilities
- Work on complex and extremely varied data sets from some of the worlds largest organisations to solve real world problems
- Develop data science products and solutions for clients as well as for our data science team
- Write highly optimized code to advance our internal Data Science Toolbox
- Work in a multi-disciplinary environment with specialists in machine learning, engineering and design
- Focus on modelling by working alongside the Data Engineering team
- Add real-world impact to your academic expertise, as you are encouraged to write papers and present at meetings and conferences should you wish
- Take part in R&D (video R&D at QuantumBlack); attend conferences such as NIPS and ICML as well as data science retrospectives where you will have the opportunity to share and learn from your co-workers
- Work in one of the most advanced data science teams globally
- How successful projections on real world problems across a variety of industries are completed through referencing past deliveries of end to end machine learning pipelines
- Build products alongside the Core engineering team and evolve the engineering process to scale with data, handling complex problems and advanced client situations
- Best practices in software development and productionise machine learning by working with our Machine Learning Engineering teams which optimise code for model development and scale it
- Work with our UX and Visual Design teams to interpret your complex models into stunning and user-focused visualisations
- Using new technologies and problem-solving skills in a multicultural and creative environment
Real-World Impact No project is ever the same; we work across multiple sectors, providing unique learning and development opportunities internationally.
Fusing Tech & Leadership We work with the latest technologies and methodologies and offer first class learning programmes at all levels.
Multidisciplinary Teamwork - Our teams include data scientists, engineers, project managers, UX and visual designers who work collaboratively to enhance performance.
Innovative Work Culture Creativity, insight and passion come from being balanced. We cultivate a modern work environment through an emphasis on wellness, insightful talks and training sessions.
Striving for Diversity With colleagues from over 40 nationalities, we recognise the benefits of working with people from all walks of life... check out our Women Transforming Tech highlights reel and our Kedro playlist
Qualifications
- Bachelor's, masters or PhD level in a discipline such as computer science, machine learning, applied statistics, mathematics, engineering or artificial intelligence
- Up to 3 years of professional experience in applying machine learning and data mining techniques to real problems with copious amounts of data
- Programming experience (focus on machine learning) R and/or Python (must), SPSS, SAS, Ruby, Hadoop (valued)
- Data treatment/data mining, e.g. SQL, AWK, Access, Spark, Excel (highly valued)
- Statistical knowledge is a plus
- Demonstrated aptitude for analytics
- Proven record of leadership in a work setting and/or through extracurricular activities
- Ability to prototype statistical analysis and modeling algorithms and apply these algorithms for data driven solutions to problems in new domains
- Ability to independently own and drive model development, balancing demands and deadlines
- Demonstrated aptitude for analytics
- Good presentation and communication skills, with the ability to explain complex analytical concepts to people from other fields
- Willingness to travel
