Data Scientist Junior jobs in United Kingdom
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EMEIA Sales Finance Data Scientist
Job summary
A leading technology company in the UK is seeking a Data Scientist to provide data and automation infrastructure for commercial insights. This role requires 5 years of experience in machine learning, strong proficiency in Python and SQL, and the ability to collaborate with cross-functional teams. The successful candidate will drive AIML adoption and focus on areas such as forecasting and data pipeline management, leveraging advanced analytics tools.
Qualifications
- 5 years of hands‑on experience building and deploying machine learning models in a production environment.
- Strong proficiency in Python and its core data science libraries.
- Strong proficiency in SQL with hands‑on experience in modern data platforms.
Responsibilities
- Collaborate with cross-functional teams to solve challenging problems.
- Drive AIML adoption across Sales Finance.
- Focus on forecasting, anomaly detection, and data pipeline management.
Skills
Education
Tools
Our team provides data & automation infrastructure to enable commercial insights for EMEIA Sales Finance. We are superusers of analytics & BI platforms (e.g. Tableau SAP BusinessObjects and various internal tools) databases (e.g. Dremio Snowflake) and data science platforms (e.g. Dataiku). We help to train others and encourage adoption of these technologies in the wider EMEIA Sales Finance a Data Scientist you will collaborate with cross-functional teams of finance analysts project managers and other data scientists to solve some of our most challenging problems and drive AIML adoption across Sales Finance. Focus areas include forecasting & disaggregation anomaly detection generative AI and data pipeline management.
- 5 years of hands‑on experience building and deploying machine learning models in a production environment.
- Strong proficiency in Python and its core data science libraries (e.g. pandas scikit‑learn statsmodels NumPy PyTorch TensorFlow LightGBM).
- Strong proficiency in SQL with hands‑on experience querying and manipulating data in modern data platforms like Snowflake or Dremio.
- Experience in developing and maintaining data pipelines.
- Demonstrable experience with MLOps principles and tools including workflow orchestration frameworks (e.g. Metaflow).
- Experience in applying machine learning techniques to provide solutions to real business problems including for time series forecasting.
- Solid understanding of the theory behind statistical analysis and machine learning.
- Experience with cloud data science platforms : Dataiku (preferred) DataRobot Databricks AWS SageMaker Google Cloud AI Platform etc.
- Basic experience with deploying infrastructure on cloud platforms like AWS or GCP.
- Basic knowledge and understanding of software design principles and how to apply them (SOLID DRY modularity abstraction consistency etc.)
- Experience in full data science project delivery lifecycle - from identifying the underlying business needs to delivering projects in a manner that meets those needs.
- Curiosity to understand new data science tools and how they can be leveraged to meet business needs.
- Ability to translate technical content for non-technical audiences and vice-versa.
- Strong verbal / written communication skills.
- Creativity to go beyond current tools to deliver the best solution to the problem.
- Detail oriented and self-motivated individual able to function effectively when working independently or in a team.
- BS / MS in Data Science / Machine Learning Mathematics Statistics Information Systems or related field
- Familiarity with MLOps practices is a plus
- Experience with Git is a plus
- Experience using Tableau is a plus
- Experience using BusinessObjects is a plus
Laboratory Experience,Immunoassays,Machine Learning,Biochemistry,Assays,Research Experience,Spectroscopy,Research & Development,cGMP,Cell Culture,Molecular Biology,Data Analysis Skills
Employment Type : Full Time
Experience : years
Vacancy : 1
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.