Lead Data Scientist required to set up and lead a new team of Data Scientists with Galway multinational.
To be considered for this role you must have several years experience in a Data Scientist role in industry AND have leadership experience. Graduates will not be considered for this role.
Responsibilities:
- Lead and drive projects from start to finish, to develop insights to facilitate business decisions.
- Build a team that can deliver our vision
- Use cutting edge cloud technologies, state of the art Machine Learning techniques and complex statistical models to leverage data, drive decisions and improve predictability and optimisation at scale.
- Collaborate with cross functional product, data and engineering teams to define problem statements and design analytical solutions.
- Interpret results, create insights and translate problems into impactful metrics and visualisations.
- Statistical data exploration, preparation
- Degree/Masters in Data Science, Mathematics, Physics
- Knowledge of tools like Python/R, Tableau and SQL
- Breath ands depth of knowledge in the areas of Statistical computing languages as tools, conventional languages (C, Java, Python, SQL)
- Sufficient knowledge of machine learning modeling techniques
- Experience visualizing model outputs for engineers, customers and stakeholders
- Experience in statistical inference, unsupervised machine learning, supervised machine learning, reliability/survivability models, and/or predictive maintenance
- Good understanding of large-scale data mining and machine learning techniques for clustering, classification, regression, and anomaly detection
- Ability to manipulate and visualize both structured and non-structured datasets
- Project leadership, management of project team, sizing and estimation of project timelines and cost
- Understanding of automotive engines and their performance would be an advantage to any candidate
- Strong analytical skills relating to unstructured data sets
- Strong experience modelling machine and behavioural data
- Proficient with machine learning techniques
- Experience with a wide variety of statistical computer languages and data mining tools
- Hands-on experience with cloud based architectures and software stacks
- Deep understanding of large always-on enterprise system architecture
- Algorithim optimisation proficiency
