Data Scientist

Manchester, England, United Kingdom

12/20/2024

Job Description

Job Summary:

We are looking for a talented Data Scientist who can characterise business

problems, develop data-driven solutions, and communicate insights effectively to

stakeholders. The successful candidate will have a strong foundation in statistics,

programming skills, and experience with big data platforms. This role requires

excellent problem-solving skills, leadership abilities, and the ability to work

collaboratively with teams.

Requirements

• Education: Bachelor's/Master's degree in Machine Learning or Computer
  
  

Science, Statistics, or related field. Preference will be given to those

candidates with strong educational background as well as relevant

certifications in the mentioned fields.

• Skills:
  
  

○ Strong foundation in statistics and programming (R/Python).

○ Experience with data preparation, visualisation, and model building.

○ Knowledge of big data platforms (Hadoop, Spark) and SQL/NoSQL

databases.

• Experience: 3+ years of experience as a Data Scientist or related role.
  
  

Typical Responsibilities

Develop and maintain data products. Data Engineering teams are responsible for

the delivery and operational stability of the data products built and provide

ongoing support for those products. Data Engineers work within, and contribute

to, the overall data development lifecycle process as part of multi-functional Agile

delivery teams focused on one or more products.

Data Scientists Should Have The Following Skills

• Data science foundation - a data scientist must be able to:
  
  

– Characterise a business problem

– Formulate a hypothesis

– Demonstrate the use of methodologies in the analytics cycle

– Plan for the execution

Understanding the data science workflow and recognizing the importance of

each element of the process is critical for successful implementations.

• Statistics and programming foundation (Analysis & Visualisation) - the
  
  

competencies in this area are focused on the knowledge of key statistics

concepts and methods essential to finding structure in data and making

Predictions. Programming Skills (R/Python) Or Other Statistical Programming

skills are essential —and the ability to visualise data, extract insights and

communicate the insights in a clear and concise manner.

• Data preparation - to ensure usable data sets, the key competencies required
  
  

Are

– Identifying and collecting the data required

– Manipulating, transforming and cleaning the data

A data scientist must deal with data anomalies such as missing values,

outliers, unbalanced data and data normalisation.

• Model building - this stage is the core of the data science execution, where
  
  

different algorithms are used to train the data and the best algorithm is

Selected. A Data Scientist Should Know

– Multiple modelling techniques

– Model validation and selection techniques

A data scientist must understand the use of different methodologies to get

insight from the data and translate the insight into business value.

• Model deployment - an ML model is valuable when it’s integrated into an
  
  

existing production environment and used to make business decisions.

Deploying a validated model and monitoring it to maintain the accuracy of the

results is a key skill.

• Big data foundation - a data scientist deals with a large volume of structured
  
  

and unstructured data, they must demonstrate understanding of how big data

is used, the big data ecosystem and its major components. The data scientist

must also demonstrate expertise with big data platforms, such as Hadoop and

Spark and master SQL and NoSQL.

• Leadership and professional development - data scientists must be good
  
  

problem solvers. They must understand the opportunity before implementing

the solution, work in a rigorous and complete manner, and explain their

findings. A data scientist needs to understand the concepts of analysing

business risk, making improvements in processes and how systems

engineering works.

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