Data Scientist (9 Months Fixed Term Contract)

ZipRecruiter; City of Edinburgh; On-site; GBP 45,000 - 60,000; Full time

Job summary

A data science recruitment firm in Edinburgh seeks a Data Scientist on a 9-month fixed-term contract. You will utilize data science techniques to address challenges related to electric vehicle adoption and customer behavior. The ideal candidate should have strong experience in building machine learning models using Python and statistical analysis skills. This role demands effective communication and collaboration with stakeholders to deliver actionable insights.

Qualifications

• Strong experience in building machine learning models and applying data science techniques using Python.
• Experience in data manipulation and statistical analysis across industries.
• Proven impact of insights and analysis on business decisions.
• Ability to communicate effectively with technical and non-technical audiences.

Responsibilities

• Build machine learning models to gain insights into customer behaviour, predict scheme misuse, EV transition, and affordability.
• Provide insights into customer preferences using statistical methods.
• Create dashboards to communicate key insights.
• Analyse customer research data using NLP techniques.
• Educate stakeholders about modelling processes.
• Support ad hoc requests for customer insights.

Skills

Building machine learning models

Data manipulation

Statistical analysis

Programming in Python

SQL querying skills

NLP techniques

Education

Degree in applied statistics, data science, or mathematics

Tools

Python

SQL

Snowflake

Sagemaker

Job description

Job Description

9 Months Fixed Term Contract

The Data Science role is responsible for using data science and modelling techniques to address critical questions for both the business and our customers. This includes understanding challenges related to electric vehicle (EV) adoption, assessing how rising costs impact customer affordability, and identifying key data points indicating potential misuse of the Scheme. The primary focus of this role is to help resolve these issues.

The role is within the Data Science and Analytics team and will focus on using data to identify potential misuse of the Motability Scheme.

The postholder will collaborate with key stakeholders to understand and define data requirements that support business decision-making on these issues. Daily tasks include applying technical skills to deliver analyses on customer behaviour, and translating these analyses into actionable insights for the business.

Responsibilities

1. Build machine learning models to gain insights into customer behaviour, predict scheme misuse, EV transition, and affordability.
2. Provide insights into customer preferences using statistical methods such as regression and hypothesis testing.
3. Create dashboards to communicate key insights on customer behaviour.
4. Analyse customer research data using NLP techniques like sentiment analysis and topic modelling.
5. Educate stakeholders about modelling processes, assumptions, and methodologies.
6. Support ad hoc requests for customer insights from the business.

About You

The ideal candidate will have:

• Strong experience in building machine learning models and applying data science techniques using Python.
• Experience in data manipulation and statistical analysis across industries.
• Proven impact of insights and analysis on business decisions.
• Strong programming skills in Python and SQL, familiarity with cloud platforms like Snowflake and Sagemaker.
• Ability to communicate effectively with technical and non-technical audiences and stakeholder management skills.

Minimum criteria include:

• Degree in applied statistics, data science, or mathematics.
• Experience with machine learning solving business problems involving structured and unstructured data.
• Experience with cloud data stores such as Snowflake and SQL querying skills.
• Strong analytical and problem-solving capabilities.

Team and Stakeholders

You will work with Data Scientists and Analysts within the Customer Insights and Analytics team, and collaborate with experts across Insurance, repairs, operations, and customer services to understand business needs and communicate insights effectively.