Senior Data Scientist – Active DV, Hybrid

Sanderson Government & Defence; Corsham; Híbrido; GBP 70 000 - 110 000; Tempo integral

Resumo da oferta

Sanderson Government & Defence is seeking a Senior Data Scientist to join our defence team in a hybrid role, with two days a week in Corsham. The role requires active DV clearance and sole UK nationality.

You will turn high-volume data into actionable insights to support mission-critical decisions for government and MOD stakeholders. You will design and deploy data science solutions, build scalable pipelines with PySpark, and translate operational needs into robust analytical approaches

Qualificações

• Proficient Python for data analysis and modelling.
• Advanced SQL for querying large datasets.
• Hands-on PySpark experience in distributed processing.
• Experience delivering data science solutions in a senior/lead capacity.
• Strong ability to communicate complex findings clearly.
• Active DV clearance or ability to obtain it.

Responsabilidades

• Design, build and deploy data science and ML solutions for defence and security use cases.
• Develop scalable data pipelines and analytics using PySpark on large, complex datasets.
• Translate operational requirements into clear analytical approaches.
• Present findings to technical and non-technical stakeholders, including senior customers.
• Mentor junior team members and promote best practices in code quality and reproducibility.
• Work within secure environments, adhering to security and data-handling policies.

Conhecimentos

Python

SQL

PySpark

Lead & mentoring

Clear communication

Active DV clearance

Descrição da oferta de emprego

Sanderson Government & Defence is seeking a Senior Data Scientist to join our defence team in a hybrid role, with two days a week in Corsham. The role requires active DV clearance and sole UK nationality.

You will turn high-volume data into actionable insights to support mission-critical decisions for government and MOD stakeholders. You will design and deploy data science solutions, build scalable pipelines with PySpark, and translate operational needs into robust analytical approaches