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Data Science Analyst

Date: Jan 5, 2021

Location: Kilkenny, KK, IE, R95 E866

Company: Glanbia

 

Glanbia Business Services

Data Science Analyst

An opportunity has arisen for a Data Scientist to join the Glanbia Centre of Excellence for Business Intelligence and Data Analytics. This is a permanent position and will report to Senior BI Data Analyst. The role can be based from either our Kilkenny or Dublin locations but will be remote to begin with.

 

Overview

The Data Scientist will be responsible for modelling complex business problems and uncovering business insights through the use of statistical, algorithmic, mining, and visualization techniques. The candidate will contribute to building and developing the organization’s data infrastructure and supporting the senior leadership with insights, management reports, and analysis for decision-making processes.

 

This is an exciting opportunity to join a dynamic team that is delivering big insights for Glanbia. The team has established a reputation for developing innovative and impactful data solutions across the multiple functions and business models within the organisation. The successful candidate will help expand the capability and capacity of the team and will take lead roles in key strategic data analytics projects. Some travel may be required for this role.

 

Key Responsibilities

  • Building production ready analytical applications to generate insight, recognise patterns, predict behaviour and deliver content directly to users of information products.
  • Translate business needs into data science and/or reporting requirements to support executive decisions with required information.
  • Perform large-scale experimentation to identify hidden relationships between variables in large datasets using structured and/or unstructured data.
  • Research and implement cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence to make analysis and modelling activities more efficient, impactful and insightful.
  • Determine requirements that will be used to train, test and validate machine learning models and/or algorithms.
  • Choose the most appropriate techniques (based on business need and available data), to develop custom data models and algorithms. As part of that, you will monitor, develop and/or create processes and production ready tools to analyse model performance and accuracy on an ongoing basis.
  • Work within cross-functional teams to develop and deploy models in an Azure/Databricks environment.

 

Qualifications

  • Minimum Primary Degree and Masters/PhD qualification in Mathematics, Statistics, Computer Science, Data Science or a related quantitative discipline.

 

Experience

  • Minimum of 2 years professional post qualification work experience in the area of data science or business analytics
  • Knowledge and experience in modelling techniques and advanced applied skills e.g. significance testing, GLM/regression, statistical forecasting, clustering, decision trees, neural networks.
  • Knowledge and experience using open source technologies such as R or Python.
  • Good knowledge of SQL and experience performing ETL using SQL/Hive SQL.
  • Demonstrable ability to write high-performance, reliable and maintainable code.
  • Experience working with reporting and visualisation tools (e.g. Tableau, d3, Power BI, Business Objects etc.).
  • Experience working in an Azure / Databricks environment is desirable.
  • Experience working within the Hadoop ecosystem (Cloudera or HortonWorks), including in-memory solutions (e.g. SAP HANA and Apache Spark) is an advantage.
  • Knowledge and experience with a version control system (e.g. Git) is desirable.

 

Competencies

  • Logical thinker with a pro-active attitude, problem solving skills and demonstrable experience working with structured and unstructured datasets.
  • Good knowledge of database structures, theories, principles, and practices generally.
  • Demonstrable experience manipulating, processing and extracting value from large (disconnected) datasets using both structured and unstructured data.
  • Good organizational skills with experience supporting cross-functional teams.