DATA SCIENTIST

i2 Group, a Harris Computer company, are seeking a skilled Data Scientist to help us enhance our i2 products and services, which are used around the world by national security, law enforcement, military, and commercial organisations. 

The ideal candidate will possess a strong background in statistical analysis, data manipulation, and machine learning, enabling them to extract valuable insights from large and complex datasets. If you are passionate about creating efficient and scalable solutions, and are eager to collaborate within a fast-paced environment, we encourage you to apply. 

This permanent position will be performed on a remote basis with a requirement to visit the i2 Office in Cambridge, UK as and when there is a business need to do so (circa 2 days per month). 

Responsibilities 

• Collaborate with cross-functional teams to understand business objectives and formulate data-driven solutions. 

• Clean, preprocess, and analyze large datasets to uncover meaningful patterns, trends, and insights. 

• Develop and implement machine learning models for predictive and prescriptive analysis. 

• Conduct exploratory data analysis to generate hypotheses and guide further research. 

• Stay updated with the latest advancements in data science and machine learning, and apply relevant techniques to solve real-world problems. 

• Communicate findings and results effectively to both technical and non-technical stakeholders through visualizations, reports, and presentations. 

• Collaborate with data engineers to ensure data availability, quality, and reliability for analysis. 

• Participate in the development of data-driven products and solutions from conception to deployment.

Requirements 

• Master's or PhD in Data Science, Computer Science, Statistics, or a related field. 

• Proven experience as a Data Scientist or similar role, showcasing successful implementation of machine learning models and data-driven solutions. 

• Proficiency in programming languages such as Python or R for data analysis and model development. 

• Strong understanding of statistical analysis, hypothesis testing, and experimental design. 

• Hands-on experience with data manipulation libraries (e.g., pandas, numpy) and machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch). 

• Solid knowledge of data visualization tools (e.g., Matplotlib, Seaborn, Tableau) to effectively communicate insights. 

• Familiarity with database systems and SQL for querying and extracting data. 

• Strong problem-solving skills and the ability to think critically about complex challenges. 

• Excellent communication skills to convey technical concepts to non-technical stakeholders. 

• Experience with cloud platforms (e.g., AWS, Azure, GCP) and big data technologies is a plus. 

• Publications or contributions to the data science community are a bonus.