Data Scientist
(Permanent)

Revenue

Location: Dublin

Role Purpose:
- Solve complex real-world business problems using cutting-edge machine learning methods and techniques.
- Develop data-driven models and tools to optimise trading performance across a host of domains including pricing and recommended sort.
- Conduct exploratory analysis to generate actionable insights, identify opportunities, and enhance our understanding of consumer behaviours. 

Reporting to: Head of Data Science

Key Duties & Responsibilities

  • Developing industry leading data science solutions through:
  • Defining data requirements and extracting required data to support solution development.
  • Performing exploratory data analysis to improve understanding of underlying trends and behaviours to help inform feature engineering work and next steps in modelling process.
  • Support in the designing and development of scalable and efficient data driven solutions.
  • Input into the design decisions determining optimal data science methodologies and technologies to use to solve the problem at hand.
  • Ensuring integrity of the data science solutions in terms of the underlying statistical and economic models and assumptions.
  • Collaborating with the MLOps team in the development and deployment of proposed solutions to a live environment and tracking the effects in real time.
  • Devising statistically robust testing plans to validate effectiveness of solutions.
  • Collating results from in-market tests and validating them.
  • Effectively communicating outputs of work to other team members and business stakeholders in a manner that can be understood by both technical and non-technical audiences.
  • Work with colleagues in Revenue function to ensure they are equipped with required tools, models and resources for optimising trading performance.
  • Support the wider business with BAU tasks related to the services Data Science provide or with designing new data-driven solutions to solve their complex business problems.
  • Proactively work with wider data & technology teams to support the collection of new data and refinement of existing data sources.

Knowledge and Skills:

  • Undergraduate, M.S. or Ph.D. in a relevant quantitative field, and 3+ years’ experience in a relevant role.
  • Solid understanding of statistical modelling, algorithms, data mining and machine learning workflows.
  • Some experience or knowledge of using more advanced ML libraries (TensorFlow, PyTorch, MXnet, etc.).
  • Experience in the development or application of GenAI algorithms seen as a plus.
  • Proficient in writing well structured, robust and readable code in Python.
  • Proficient in SQL and relevant experience using relational databases.
  • Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner.
  • Proven experience manipulating and analysing complex, high-volume, high-dimensional data from varying sources.
  • Ability to create compelling visualisations and dashboards (e.g. Tableau, Thoughtspot).
  • Knowledge of Git and modern development workflows.
  • Proven ability to work creatively and analytically in a fast-paced, problem-solving environment.
  • Ability to partner with Software Engineering teams to co-develop functionality for the business.

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