Data Scientist with 4 years experience at least

ZipRecruiter; Manchester; On-site; GBP 40,000 - 80,000; Full time

Job summary

An innovative company in the data science field is seeking a talented individual with expertise in statistical modelling, machine learning, and AI. This role involves collaborating with diverse stakeholders to solve real-world problems using advanced technologies. You will play a crucial part in transforming customer operations and driving growth through insightful data analysis and visualization. If you are passionate about leveraging data science to make impactful changes and thrive in a collaborative environment, this opportunity is perfect for you.

Qualifications

• Experience in statistical modelling, machine learning, and AI.
• Ability to interpret findings for non-technical audiences.

Responsibilities

• Collaborate with customers to apply research and technology.
• Contribute to the data science team, shaping products and driving growth.

Skills

Statistical Modelling

Machine Learning

AI

Data Science

Forecasting

Optimization

R

Python

SQL

Data Visualization

Job description

Job Description

Responsibilities:

1. Experience in one or more of the following areas: statistical modelling, machine learning, AI, data science, forecasting, optimization.
2. Programming skills and the ability to quickly learn new technologies. Experience with R, Python, and other statistical tools is a plus.
3. Familiarity with relational databases and SQL at an intermediate level, as you'll work with various datasets.
4. Strong understanding of a wide range of statistical techniques.
5. Ability to interpret and present findings to non-technical audiences. Experience in data visualization and deriving insights from diverse data sources is advantageous.
6. Collaborate with customers across multiple sectors, applying research and technology to solve real-world commercial problems.
7. Contribute as a key member of the data science team, shaping products and driving growth by transforming customer operations.
8. Interface with diverse stakeholders, from academic experts to onsite clients, requiring independence and responsibility.
9. Expertise in machine learning, data science, and AI, with a commitment to staying updated on technological advances and research.
10. Communicate findings clearly to multidisciplinary teams and stakeholders.