Data Scientist

Hybrid in London·Added 4 days ago (last checked 9 Oct)

Chubb

25 open roles

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Overview

Job details

Hybrid
Office and home days — the ad has the split.

Benefits

25 days holiday
Per the ad, which doesn’t say whether bank holidays are on top.

Requirements

Be near London for hybrid days
No relocation package mentioned.
Have 3+ years of experience
Mid-level role.

Skills

Requirements

Qualifications

Bachelor’s or Master’s degree in Data Science, Mathematics, Computer Science, Statistics, Analytics, Physics, or a related field.
3+ years of experience in an analytics driven role (i.e., Data Scientist, ML Engineer, Data Analyst, etc.)
Business experience in the insurance or financial services industry is preferred but not a must.
Programming experience in Python with an understanding of object-oriented programming.
Experience using SQL for data extraction and manipulation.
Experience with development and implementation of machine learning and statistical models.
Strong communication skills – Being able to translate advanced technical topics to non-technical stakeholders but also of sustaining highly technical conversations with other engineers and developers.
Experience with tools from the following tech stack: GitHub, Python, Databricks, VSCode, MLFlow.
Experience using AI tools such as Claude Code as an enabler and productivity enhancer.

We offer in return!

Competitive salary & pension scheme, discretionary bonus scheme, 25 days annual leave plus ability to purchase 5 additional days, hybrid working options, Private Medical cover, Employee Share Purchase Plan, Life Assurance, Subsidised gym membership, Comprehensive Learning & development offerings, Employee Assistance program.

Integrity. client focus. respect. excellence. teamwork

Our core values dictate how we live and work. We’re an ethical and honest company that’s wholly committed to its clients. A business that’s engaged in mutual trust and respect for its employees and partners. A place where colleagues perform at the highest levels. And a working environment that’s collaborative and supportive.

Diversity & Inclusion. At Chubb, we consider our people our chief competitive advantage and as such we treat colleagues, candidates, clients, and business partners with equality, fairness and respect, regardless of their age, disability, race, religion or belief, gender, sexual orientation, marital status or family circumstances.

We are committed to ensuring our recruitment process is inclusive and accessible to all. If you have a disability or long-term condition (for example dyslexia, anxiety, autism, a mobility condition or hearing loss) and need us to make any reasonable adjustments, changes or do anything differently during the recruitment process, please let us know.

The role

Qualifications

Bachelor's or Master's degree in Data Science, Mathematics, Computer Science, Statistics, Analytics, Physics, or a related field.
3+ years of experience in an analytics driven role (i.e., Data Scientist, ML Engineer, Data Analyst, etc.)
Business experience in the insurance or financial services industry is preferred but not a must.
Programming experience in Python with an understanding of object-oriented programming.
Experience using SQL for data extraction and manipulation.
Experience with development and implementation of machine learning and statistical models.
Strong communication skills - Being able to translate advanced technical topics to non-technical stakeholders but also of sustaining highly technical conversations with other engineers and developers.
Experience with tools from the following tech stack: GitHub, Python, Databricks, VSCode, MLFlow.
Experience using AI tools such as Claude Code as an enabler and productivity enhancer.

We offer in return!

Integrity. client focus. respect. excellence. teamwork

Our core values dictate how we live and work. We're an ethical and honest company that's wholly committed to its clients. A business that's engaged in mutual trust and respect for its employees and partners. A place where colleagues perform at the highest levels. And a working environment that's collaborative and supportive.