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Staff Data Scientist – B2B Marketing & Attribution

Location: Dallas, TX (Onsite, relocation available)

Comp: $180-220k base + equity + bonus

A global semiconductor company is building out its internal marketing and growth analytics function and is seeking a Staff Data Scientist to lead the transformation of its B2B advertising and attribution strategy. This role is highly strategic, focused on evolving measurement capabilities from last-click attribution to a full-funnel, multi-touch approach that better captures the complexity of long sales cycles and account-based engagement. You will play a critical role in integrating audience signals, campaign performance data, and attribution models to drive more efficient customer acquisition and pipeline growth.

What You’ll Do

• Lead the design and implementation of full-funnel attribution models, transitioning from last-click to multi-touch measurement frameworks.

• Develop data-driven strategies to improve CAC, marketing efficiency, and pipeline contribution across B2B channels.

• Integrate and analyze data across platforms including DSPs, CDPs, Google Analytics (GA4), CRM systems, and the enterprise data warehouse.

• Build and scale A/B and multivariate testing frameworks to optimize campaign performance and conversion rates.

• Apply AI/ML techniques to enhance audience segmentation, targeting, and predictive performance modeling.

• Partner with marketing, sales, and product stakeholders to translate business goals into measurable analytics initiatives.

• Establish best practices around marketing measurement, experimentation, and attribution in a complex, account-based environment.

What You Bring

• 8+ years of experience in data science, with a strong emphasis on B2B marketing, advertising, or growth analytics.

• Proven experience advancing organizations from last-click to multi-touch attribution models.

• Strong programming skills in Python and SQL, with experience working in modern data warehouse environments (e.g., Snowflake, BigQuery, Redshift).

• Hands-on experience with Google Analytics, DSPs, CDPs, and ABM platforms such as 6sense or Demandbase.

• Deep understanding of CAC, funnel metrics, pipeline attribution, and campaign performance analysis.

• Experience leading experimentation strategies and applying statistical methods to measure impact.

• Ability to communicate complex analytical insights to cross-functional and executive stakeholders.

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Data Scientist

Liverpool area (3 days onsite) | £45,000 to £50,000

This is a strong opportunity for a commercially minded Data Scientist to step into a growing team at a key point in its data journey. You will have the chance to work on high-impact customer projects while helping shape how data science is delivered and scaled across the business.

The Company

They are a well-established UK retail organisation investing heavily in building a modern data and AI capability. The business is transitioning away from ad hoc analytics towards a more structured and scalable data science approach. A major focus is on customer insight and personalisation, driven by a new loyalty programme. The culture is collaborative, pragmatic, and focused on delivering tangible value.

The Role

You will work closely with the Data Science Lead and a small, high-impact team to deliver production-ready models and insights.

• Build and deploy machine learning models to support customer and commercial decision making
• Deliver key use cases such as customer segmentation, lifetime value modelling, and demand forecasting
• Work across the full data science lifecycle from problem definition through to deployment
• Contribute to the development of a new data science platform
• Collaborate with data engineers, analysts, and business stakeholders to deliver measurable impact
• Communicate complex findings clearly and confidently to non-technical audiences
• Support scaling existing models into broader business use

Your Skills and Experience

• Strong commercial experience applying data science and machine learning to business problems
• Proficiency in Python preferred, or R with openness to transition
• Solid SQL skills and experience working with complex datasets
• Experience delivering end-to-end data science solutions, including production deployment
• Exposure to cloud platforms such as GCP or Azure is beneficial
• Strong stakeholder management and communication skills
• A practical, outcome-focused approach to problem solving

What They Offer

• £45,000 to £50,000 salary
• Hybrid working with 3 days onsite in the Liverpool area
• The opportunity to shape and influence a growing data science function
• Clear progression as the team scales
• Collaborative and inclusive working environment
• Benefits including staff discount, wellbeing support, pension, and development opportunities

How to Apply

Apply now with your CV to explore this opportunity further.

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Data Scientist

Knowsley – 3 days a week

The Company
They are a well established UK retail business undergoing a broader data and AI transformation. The organisation is investing in building a modern Data Science capability to support decision making across commercial and customer functions. Their culture is practical, collaborative and delivery focused, with an emphasis on creating value quickly rather than over engineering solutions. Data is increasingly central to their strategy, particularly with the launch of a new customer loyalty programme.

The Role
You will work closely with the Data Science Lead and a small but growing team to develop and productionise machine learning solutions.

• Build and deploy models that support customer and commercial decision making
• Work on use cases such as customer segmentation, lifetime value modelling and demand forecasting
• Contribute to the development of a scalable Data Science platform
• Collaborate with data engineers, analysts and business stakeholders
• Translate business problems into data science solutions and clearly communicate outputs
• Support the expansion of existing models into broader production use

Your Skills and Experience

• Strong commercial experience in Data Science using Python
• Solid SQL skills and experience working with large datasets
• End to end experience delivering Data Science solutions from problem definition through to deployment
• Experience building and validating machine learning models
• Ability to communicate insights clearly to non technical audiences
• A practical, business focused approach to problem solving

What They Offer

• Hybrid working with three days per week in Knowsley
• Opportunity to shape and influence a growing Data Science function
• Exposure to end to end project work with real business impact
• A collaborative environment focused on learning and delivery

How to Apply
Apply now to learn more about this Data Scientist opportunity and the impact you can make within a growing data driven environment.

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Data Scientist – Merseyside

As a Data Scientist, you will work closely with the Lead Data Science and cross-functional teams to develop and deploy models that support customer and commercial decision-making. Responsibilities include:

• Building and deploying machine learning models across customer use cases
• Delivering projects focused on customer segmentation, lifetime value, and forecasting
• Supporting targeted marketing activity, including campaigns and personalisation
• Collaborating with data engineers, analysts, and business stakeholders
• Contributing to the development of a scalable Data Science platform
• Ensuring models are production-ready and drive measurable business impact

Your Skills & Experience

• Strong commercial experience in Data Science, delivering end-to-end projects
• Proficiency in Python, with solid SQL skills
• Experience applying machine learning and statistical techniques to business problems
• Exposure to deploying models into production environments
• Understanding of cloud platforms such as GCP or Azure is beneficial
• Ability to communicate insights clearly to non-technical stakeholders
• A practical, delivery-focused mindset with a collaborative approach

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Head of Data Science
London (Hybrid, 2 to 3 days per week)

This is a high-impact leadership opportunity to shape how a major consumer business uses data to drive growth, improve decision making, and deliver measurable value. You will lead the integration of data science and analytics into a single, high-performing function while influencing senior stakeholders and setting a clear strategic direction.

The Company
They are a well-established, customer-focused organisation undergoing a significant data transformation. With strong investment and leadership support, data is central to their future strategy. The business operates in a fast-paced, commercially driven environment and places high value on innovation, experimentation, and measurable outcomes. Data maturity is still developing, creating a genuine opportunity to shape the roadmap and drive meaningful change.

The Role
You will take ownership of the data science and analytics capability, focusing on both strategy and execution. Key responsibilities include:
* Defining and delivering the data science and analytics strategy aligned to wider business goals
* Driving the adoption of self-serve analytics tools and improving data accessibility across teams
* Leading the redesign and optimisation of reporting, dashboards, and insight delivery
* Overseeing development, productionisation, and deployment of data science solutions
* Embedding performance frameworks to measure value, impact, and business outcomes
* Building and scaling a high-performing, multidisciplinary team across data science and analytics
* Engaging and influencing senior stakeholders, including CIO and COO level
* Shifting perception of data science from a support function to a core value driver

Your Skills and Experience
You will bring a strong combination of technical depth, leadership capability, and commercial awareness:
* A background as a data scientist with strong attention to detail and the ability to challenge methodologies
* Deep understanding of data science techniques, principles, and underlying mathematics
* Strong experience delivering data science solutions across multiple domains in commercial settings
* Proven ability to build, develop, and lead high-performing teams
* Experience operating in environments with low or evolving data maturity
* Excellent stakeholder management skills, with the ability to translate complex concepts into clear business narratives
* Strong track record of delivering measurable business impact from data initiatives
* Comfortable working in ambiguous, fast-changing environments and driving transformation

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Graduate Data Scientist

London – 4 days a week

The Company
They are a modern, data-driven insurance provider focused on delivering flexible, tailored policies to customers. The business has expanded its product offering and built strong commercial partnerships, driving rapid growth. With around 100 employees, they are scaling quickly and investing heavily in advanced analytics and modelling. The culture is collaborative, fast-paced, and centred on innovation.

The Role
As a Graduate Data Scientist, you will work on models that sit at the core of the business and support key commercial decisions.

• Develop predictive models across pricing, risk, and customer acquisition
• Build clustering and segmentation models to support strategic decision-making
• Analyse large and complex datasets to uncover actionable insights
• Collaborate with analysts and engineers to deploy and productionise models
• Contribute to a greenfield modelling environment and help shape best practices
• Take ownership of projects with visibility across the wider business

Your Skills and Experience

• Strong academic background in a STEM subject such as Mathematics, Data Science, Computer Science, or similar
• Solid programming skills, ideally in Python
• Understanding of statistical modelling and machine learning fundamentals
• Hands-on experience through internships, placements, or personal projects
• Demonstrated curiosity and initiative, such as side projects or GitHub work
• Clear communication skills and the ability to collaborate with cross-functional teams
• Motivated, proactive, and keen to take ownership early in your career

What They Offer

• Hybrid working with a strong in-office culture
• Opportunity to work on high-impact, business-critical models
• Fast career progression as the team continues to grow
• Work abroad flexibility for short periods each year
• Supportive environment with strong learning and development opportunities

How to Apply
If you are a graduate or early-career data scientist looking to make an impact in a high-growth environment, please apply with your CV.

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Graudate Data Science Role

This is an excellent opportunity to join a fast-growing, data-driven insurance business that is transforming how pricing and risk are approached. With strong investment in analytics and a high-performing team already in place, you will have the chance to work on impactful pricing problems while developing your skills in a highly commercial environment.
You will join the pricing team, playing a key role in analysing customer data and supporting pricing strategy.

The Role:

• Develop and refine pricing models to optimise customer acquisition and retention
• Analyse large datasets to identify trends and inform commercial decisions
• Collaborate with stakeholders to translate business requirements into data solutions
• Contribute to model development and testing within a regulated environment
• Support ongoing improvement of pricing processes and methodologies
• Work in a fast-paced team, delivering insights with real business impact

Your Skills and Experience

• Strong academic background in a quantitative discipline such as Mathematics or Physics
• Proven ability to work with data and build analytical models
• Experience or interest in pricing, insurance, or closely related commercial analytics
• Strong problem-solving skills, with the ability to think logically and clearly
• Comfortable communicating technical ideas to non-technical stakeholders
• Strong attention to detail and a structured approach to analysis

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