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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in managing data science and machine learning projects, utilizing Python and SQL for data exploration and model development, while effectively communicating insights to both technical and non-technical stakeholders. Proven ability to implement machine learning models in production environments and leverage AI tools for innovative solutions.
Highest-signal resume keywords
Machine Learning Project ManagementPython ProgrammingSQL ProficiencyClient Services SkillsStatistical Analysis
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningData ExplorationModel EstimationData VisualizationStatistical KnowledgeLLM ExperienceCloud DeploymentWeb AnalyticsMarketing AnalyticsDigital Marketing
Soft Skills
Communication SkillsTime ManagementOrganizational Abilities
Tools & Technologies
AI ToolsClaude CodeML Libraries
Certifications & Qualifications
Master's DegreePhD
Industry Keywords
Quantitative DisciplinesMarketing Effectiveness MeasurementMarketing Optimization Techniques
Tech Stack
Tools & technologiesCloudPythonSQL
About the role
Key responsibilities & impact- Manage data science and machine learning projects so technical goals are met within agreed timeframes
- Communicate work clearly with clients and team members
- Produce explanatory insights for non-technical users through visualizations, metrics and tabulations
- Interface with clients to obtain required data inputs and explain service application
- Explore and model large datasets using Python, SQL and related tools
- Leverage AI tools including Claude Code to develop and enhance solutions
- Lead data exploration, model estimation and validation
- Write clean, efficient, robust and well-commented code
- Discuss data science aspects with technical and commercial teams
- Work with data engineers to scale algorithmic work
- Communicate analytics methodologies to clients and internal stakeholders
- Spend around 20% of time on innovation supporting product development and agentic AI goals
Requirements
What you’ll need- Master's degree or PhD, or relevant experience in a field emphasizing quantitative disciplines, with coursework in machine learning; alternatively, a quantitative advanced degree complemented by extensive training in data science/ML
- Proven experience in applied machine learning through a prior full time role
- Knowledge and experience of Python, associated ML libraries and SQL
- Experience using LLMs to help systematically write and review safe and stable code
- Strong statistical knowledge
- Ability to communicate data analysis and modeling results
- High level of proficiency in English writing and speaking
- Strong client services skills
- Strong time management and organizational abilities
- Experience with putting machine learning models into production in a cloud environment
- Knowledge and experience of marketing effectiveness measurement and marketing optimisation techniques
- Experience in web analytics, marketing analytics and digital marketing
- Experience working with senior stakeholders in an analytics context
Benefits
Comp & perks- Sabbatical: Paid sabbatical at 7 years with an option to take it unpaid at 5 years
- 25 days holiday a year
- Discretionary annual performance based incentive
- Sale commission
- Recruitment referrals bonus
- Health & Wellbeing contribution
- 2 Recharge Days each holiday year
- Ride to Work scheme
- Railcard Season Ticket loan
- Home office screen
- Free fruit, breakfast cereals, snacks, and tea & coffee
- Complimentary lunch every week
- Enhanced Primary and Secondary family leave as well as extended Parental Leave and Shared Family Leave
- Life insurance and income protection
- Medical Cash Plan
- Pension
- Curated 3rd party learning platform and access to Croud Campus
- Peer to peer recognition scheme 'bonusly'
- Team off-sites/regular socials
- Year-round holiday parties
- Flexible working options
- Day to make a difference