Bỏ qua để đến phần nội dung

Cổng thông tin nghề nghiệp

Data Science Analyst

Opportunity: Data Science Analyst

Location: Stockley Park, UK

Summary of role:
As Coats is moving from the Industrial age to the Digital age, harnessing the power of data and analytics become very critical. Especially if Coats is to become a digital leader. 

For this reason, Coats established the new Data Science Division. Data Science is the forefront of harnessing the power of data and analytics. Unlike traditional data analytics which focuses on reporting and basic analysis, Data Science focuses on predictive and prescriptive analysis. It predicts what will happen and provides suggestion what should happen. Data Science will move Coats from hindsight to foresight. 

Data Science, through application of advanced mathematics and cutting-edge technology, can significantly improve business performance. Various researches, e.g. by McKinsey and SAP, suggest that:
  • Organisations are seeing sizable return of investment from their data science projects. The average potential impact is between $1m-$100m. Its application range from fraud detection, increased sales, to cost saving. 
  • There are significant untapped potential from data science. For manufacturing companies, the estimated potential impacts are up to 50% lower product development cost, 25% lower operating cost, and 30% gross margin increase. 
The purpose of the Data Science Analyst is to enable Coats to tap the significant potentials of data and data analytics.

Key accountabilities:
The principal accountabilities of the Data Science Analyst is as follow: 
  • Responding to advanced data analytics requests from the businesses.
The key activities of the Data Science Analyst are:
  • Understand challenges faced by the businesses / the required performance improvements.
  • Identify data sources, assess data accuracy and consistency, and determine required data.
  • Extract and prepare data for analytics.
  • Employ advanced mathematical modelling and artificial intelligence to generate insights.
  • Develop recommendation of actions, options and decisions based on the insights (implementation of actions, change management, and process reengineering to be managed by the respective business).
  • Monitor the actual performance improvements and tweak the model if required.
In order to be effective, the Data Science Analyst must:
  • Think strategically and critically – see the big picture and focus on key impacts.
  • Have business experience and business sense – can identify significant opportunities. 
  • Have understanding of machine learning, data mining, multivariate statistical analysis, mathematical modelling and operation research.
The performance of the Data Science Analyst are measured by these high level KPIs:
  • Measured performance improvement from the applications.
  • Internal customer satisfaction.
Education, Qualifications and Experience:
  • Experience in the area of Data Science for business improvement. Can identify business opportunities, know how to apply data science for business problem, know how to deliver solutions for business.
  • Knowledge of various machine learning, data mining, multivariate statistical analysis, mathematical modelling and operation research techniques. 
  • Strong communication skill – orally and written. Can convey complex idea in easy to understand explanation. 
  • Work well independently or within team. Can work well with various stakeholders across the Group to deliver the required improvements. 
  • Experience in using R / Python for Data Science. Experience in handling Big Data. Familiar with Hadoop / Spark.
  • Understand Coats' data structure and systems. Familiar working with SAP, SFDC, and eComm. Know how to deal with multiple data sources, including external data sources.
  • Experienced in using SAP Predictive Analytics.
  • Experienced in using Azure Machine Learning.
  • Degree related to Business Management or Data Science.