- Maintain clear and coherent communication, both verbal and written, to understand data needs and report results
- Create clear reports that tell compelling stories about how customers or clients work with the business
- Assess the effectiveness of data sources and data-gathering techniques and improve data collection methods
- Conduct research from which you’ll develop prototypes and proof of concepts
- Establish new systems and processes and look for opportunities to improve the flow of data
- Evaluate new and emerging technologies
- Represent the company at external events and conferences
- Build and develop relationships with clients
- Identify valuable data sources and automate collection processes
- Undertake pre-processing of structured and unstructured data
- Analyse large amounts of information to discover trends and patterns
- Build predictive models and machine-learning algorithms
- Combine models through ensemble modelling.
- Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
- Mine and analyse data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
- Assess the effectiveness and accuracy of new data sources and data gathering techniques.
- Develop custom data models and algorithms to apply to data sets.
- Use predictive modelling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
- Develop company A/B testing framework and test model quality.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Develop processes and tools to monitor and analyse model performance and data accuracy.
Experience
- 5-7 years of experience manipulating data sets and building statistical models
- Strong problem-solving skills with an emphasis on product development
- Experience using statistical computer languages to manipulate data and draw insights from large data sets
- Experience working with and creating data architectures
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications
- Excellent written and verbal communication skills for coordinating across teams
- Knowledge and experience in statistical and data mining techniques
- Experience querying databases and using statistical computer languages
- Experience using web services
- Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modelling, clustering, decision trees, neural networks, etc.
- Experience analysing data from 3rd party providers
- Experience with distributed data/computing tools
- Experience in visualizing/presenting data for stakeholders
Qualifications A degree, Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field, with the following degree subjects:
- Computer science
- Data science/computer and data science
- Engineering
- Mathematics and operational research
- Physics
Technical Skills
- Statistical analysis and computing
- Machine Learning
- Deep Learning
- Processing large data sets
- Data Visualization
- Data Wrangling
- Mathematics
- Programming