Data Scientist

Company:
Location: Dublin

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Recognising the value of data to our business, we are expanding the Advanced Analytics capability in Three Ireland. This is an exciting time for the team as we grow and embark on our big data journey.

Within the Analytics & Innovation team, we are passionate about driving insight and value from data. The team work across a spectrum of exploratory analysis, feature engineering, data engineering, event prediction, data driven segmentation, deep dive analyses and development of bespoke solutions to meet business needs.

This opportunity will suit data scientist/Analyst with a strong academic background, adept at stakeholder management and an appetite for working with many disparate sources and types of data and use cases. You will join as a key member of the team with the opportunity to grow and develop your skills within a fast paced, exciting, data-rich environment.

We value innovation and creativity and this role presents a great opportunity for any analyst who has the capability to collaborate and identify business needs, approach a business problem in an innovative way, identify and build a great solution, and the ability to communicate the outputs of that work across the business.

What else it involves
Performing deep-dive analyses that help drive agile, data-driven decisions on important issues facing the business
Working cross-functionally to identify actionable insights from our rich data sources and create new tools to support the business need to drive value from our data
Building predictive and prescriptive models that are focused on impacting core KPIs across the breadth of telco verticals
Creating segmentations that allow us to better understand our customer base and what we can do to serve them better
Maintaining current market awareness within the analytics industry, proposing and building solutions to business objectives using state of the art techniques
Developing domain expertise, leading to proactive identification of use cases and activities to benefit the team and the business
Working in an agile manner, constantly seeking the most efficient methods to deliver against business objectives, delivering rapid insights and proof of concepts to stakeholders
Mentor Junior members of the team
Lead effectively on team projects as assigned
Strong stakeholder management capabilities

The skills we`re looking for:
Coming from a relevant field of study in a STEM discipline
Methodical and logical approach in understanding the data at hand
Demonstrable experience of predictive modelling and clustering techniques in a commercial
environment
Understanding of classical and new data analysis methods and the ability to identify the ideal approach to individual projects from a range of model types & methods(Ensemble, Random Forest, Neural Networks, Naive Bayes, OLS, Linear & Logistic regressions, SVM etc.)
Experience with supervised and unsupervised learning methods for model build and deployment
Knowledge of a wide range of statistical techniques, ANOVA, Regression, GLM, ARIMA etc. and clearly explains those concepts to stakeholders and draws appropriate inferences
Demonstrable statistical programming experience in R, Python, Scala, other
Strong level SQL
knowledge and comprehension of technology and data management techniques used in the process of collecting, storing and retrieving data
Strong problem-solving skills and adept at identifying solutions to use cases
Skilled in effective data visualisation constantly working to improve the use of visualisations to supplement and enhance analytical outputs
Capability to work with autonomy and in partnership with other Data Scientists to find solutions to complex problems
Exposure to deep learning frameworks such as Tensorflow, CNN, CNTK a plus
Experience in a Big Data environment desirable: Exposure to Cloudera or Hortonworks, having used tools within the Apache Ecosystem Hadoop Core such as: - HDFS, Yarn, MapReduce, Spark, Hive, Apache Nifi, Oozie, HBase, Ambari, Cloudera Manager, Kakfa etc.

*** Mention DataYoshi when applying ***

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