Data Scientist

Sage Group plc; Newcastle upon Tyne; Hybrid; GBP 50,000 - 80,000; Full time

Job summary

Join a forward-thinking company as a Data Scientist and be part of a dynamic IT team dedicated to revolutionizing data delivery. In this hybrid role, you'll leverage your expertise in machine learning and big data technologies to enhance customer experiences and optimize business processes. Collaborate with cross-functional teams to develop innovative data solutions, ensuring data integrity and fostering a culture of data-driven experimentation. This is an exciting opportunity to make a significant impact in a company recognized as one of the best places to work, where your contributions will help shape the future of business technology.

Benefits

Flexible working hours

Health insurance

Professional development opportunities

Employee discounts

Remote work options

Wellness programs

Team-building activities

Generous vacation policy

Retirement savings plan

Performance bonuses

Qualifications

• Strong proficiency in Python and SQL for data analysis.
• Experience with big data frameworks and cloud platforms.

Responsibilities

• Develop advanced analytics and machine learning models.
• Transform complex data sources into a unified version of truth.

Skills

Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow)

SQL

Apache Spark

AWS (S3, Lambda, SageMaker, Redshift)

Snowflake

MLOps principles

NLP techniques

Data visualization tools (Tableau, Power BI)

Statistical analysis

Customer analytics

Education

Degree in a quantitative discipline

Tools

Databricks

Dask

GitHub

Job description

Job Title

Data Scientist

Job Description

Exciting Job Opportunity: Data Scientist

Job Purpose: Join our dynamic IT team on a mission to revolutionise data delivery worldwide! We emphasize simplicity, mobility, and efficiency, with data and analytics at the heart of enhancing customer experiences and optimizing business processes through innovative solutions.

This role is a hybrid role - 3 days per week in our Newcastle Office

Role Overview: As a Data Scientist, reporting to the BI and Analytics Manager, you'll be a pivotal member of our BI and Analytics Hub. You'll develop advanced analytics and machine learning models to transform our understanding and prediction of customer behaviour. Using cutting-edge methodologies and big data technologies, you'll bridge business needs and technical solutions, fostering close collaboration across the organization. Your work will ensure our data-driven solutions are robust, scalable, and impactful.

Key Responsibilities

Key Contributions:

• Deliver data solutions and services that optimize customer connections across channels.
• Transform our complex IT data estate by unifying disparate data sources into a single, managed version of the truth.
• Ensure data integrity through central data mastering and modelling, enabling colleagues to interact with data to meet their needs.
• Simplify data integrations between systems via a central platform, enhancing user experience and minimizing risk.
• Promote a culture of data-driven experimentation, showcasing the value of our data through insights and analytics, and demonstrating emerging tech tools.

Additional Responsibilities include:

• Develop and own data science solutions, applying statistical/machine-learning models for segmentation, classification, optimisation, and time series analysis.
• Present findings to the wider team and organisation.
• Identify insights and suggest recommendations to influence business direction.
• Develop and optimise churn prediction models to understand customer retention patterns and implement mitigation strategies.
• Build forecasting models to predict business KPIs, customer lifetime value, and revenue trends using machine learning and statistical techniques.
• Integrate Large Language Models (LLMs) into RAG-based systems to improve knowledge retrieval and decision support for enterprise applications.
• Collaborate with data engineers to design scalable data pipelines for machine learning model deployment and inference at scale.
• Work with cross-functional teams to translate business problems into data science solutions.
• Develop ETL processes and data transformation workflows for structured and unstructured data.
• Utilise big data technologies like Spark and Snowflake to process, store, and analyse large datasets efficiently.
• Optimise and fine-tune LLMs to improve their performance within RAG systems and ensure alignment with business goals.
• Perform A/B testing and statistical analyses to validate model effectiveness and recommend improvements.
• Communicate findings and insights to stakeholders through compelling data visualizations and presentations.

Skills, Know-How, and Experience

• Strong proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow) and SQL.
• Experience with big data frameworks such as Apache Spark, Databricks, or Dask.
• Hands-on experience with cloud platforms like AWS (S3, Lambda, SageMaker, Redshift), Azure, or GCP.
• Knowledge of Snowflake, including Snowpark for scalable data processing and ML integration.
• Familiarity with MLOps principles, CI/CD pipelines, and model deployment in production environments.
• Knowledge of NLP techniques and experience with transformer-based LLMs (e.g., OpenAI, Llama, Claude).
• Strong understanding of machine learning algorithms for classification, regression, clustering, and time series forecasting.
• Experience with data visualisation tools such as Tableau, Power BI, or Python-based libraries (Matplotlib, Seaborn, Plotly).
• Excellent problem-solving skills, analytical thinking, and ability to communicate complex technical concepts to non-technical stakeholders.
• Experience in customer analytics, digital marketing, or e-commerce industries.
• Familiarity with vector databases and embedding-based retrieval techniques for RAG implementations.
• Familiarity with modern agentic AI techniques eg Model Context Protocol (MCP).

Technical/Professional Qualifications

• Degree in a quantitative discipline (applied mathematics, statistics, computer science, operations research, or related field).
• Demonstrable experience in exploratory data analysis and feature engineering.
• Experience with Python, Scikit-learn, PyTorch. Ideally, experience with PySpark, Snowflake, AWS, and GitHub (MLOps practices).

Ready to make a difference with your data science expertise? Apply now and be part of our innovative journey!

Additional Information

Function: IT

Country: United Kingdom

Office Location: Newcastle

Work Place type: Hybrid

Advert: Working at Sage means you're supporting millions of small and medium-sized businesses globally with technology to work faster and smarter. We leverage the future of AI, meaning business owners spend less time doing routine tasks, like entering invoices and generating reports, and more time pursuing their ambitions.

Our colleagues are the best of the best. It's why we were awarded 2024 Best Places to Work by Glassdoor. Because to achieve extraordinary outcomes, we need extraordinary teams. This means infusing Sage with people who knock down barriers, continuously innovate, and want to experience their potential.

Learn more about working at Sage: sage.com/en-gb/company/careers/working-at-sage/

Watch a video about our culture: youtube.com/watch?v=qIoiCpZH-QE

We celebrate individuality and welcome you to join us if you embrace all backgrounds, identities, beliefs, and ways of working. If you need support applying, reach out at [e-mail].

Learn more about DEI at Sage: sage.com/en-gb/company/careers/diversity-equity-and-inclusion/