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Analytics Engineering Manager

Location: Amsterdam, Netherlands (Hybrid)

Salary: €100-115k

This is an opportunity to lead the data foundation of a large-scale digital business where data sits at the heart of every product, analytics, and commercial decision. You will combine people leadership, technical ownership, and strategic influence while shaping a modern analytics engineering function operating at significant scale.

The Company

They are a well-established digital organisation with a strong data-driven culture and a substantial investment in data and analytics. Their teams rely on trusted, high-quality data to support decision-making across product, commercial, and leadership functions. The business is continuing to evolve its data platform, creating an opportunity for an experienced Analytics Engineering Manager to have a visible and lasting impact. You will work closely with senior stakeholders while helping to define the future direction of their data ecosystem.

The Role

You will be responsible for leading the analytics engineering capability and ensuring the data platform remains scalable, reliable, and trusted across the organisation.

Responsibilities include:

• Leading, coaching, and developing a team of Analytics Engineers and Data Engineers
• Owning data ingestion pipelines, transformation workflows, and data warehouse orchestration
• Designing and maintaining scalable data models that support analytics and business reporting
• Establishing and governing a semantic layer to ensure consistent metric definitions
• Driving automation across analytics engineering processes to improve efficiency and scalability
• Setting engineering best practices including CI/CD, code reviews, testing, and version control
• Improving platform performance, reliability, observability, and data quality standards
• Managing warehouse optimisation initiatives and controlling data platform costs
• Partnering with analytics, engineering, and business teams to align data capabilities with business needs
• Communicating platform strategy, priorities, risks, and investment requirements to senior stakeholders

Your Skills & Experience

• Strong leadership experience managing Analytics Engineering or Data Engineering teams
• Deep expertise in modern cloud-based data platforms and large-scale data warehousing environments
• Strong knowledge of ELT/ETL architecture, data modelling, and orchestration frameworks such as Airflow, dbt, or similar technologies
• Experience building reliable, observable, and well-governed data platforms
• Strong understanding of data quality, monitoring, testing, lineage, and data contracts
• Experience optimising data platform performance and managing cloud data costs
• Software engineering best practices including Git-based workflows, CI/CD, and automated testing
• Ability to balance technical leadership, delivery ownership, and people management
• Strong stakeholder management skills with the ability to communicate technical concepts to non-technical audiences
• Exposure to AI-assisted engineering workflows, automation, or productivity-enhancing tooling is advantageous
• Experience with streaming or near real-time data environments would be beneficial

What They Offer

• Opportunity to lead a strategically important data engineering function
• High levels of ownership and influence over platform direction and standards
• Exposure to complex, large-scale data challenges
• A collaborative and data-focused environment with strong executive sponsorship
• Clear opportunities for professional growth and leadership development

How to Apply

If you are an experienced Analytics Engineering Manager looking to shape the future of a modern data platform, apply now to learn more about this opportunity.

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Lead Data Engineer

Up to £100,000
*Kafka or Kinesis required
London (4 days onsite)

This is a great opportunity to join a high‑growth organisation where you can take ownership of building and architecting a greenfield data platform for an AI‑driven product.

THE COMPANY:

This is an early-stage, venture-backed company building the operating system for modern property management through its AI platform.

THE ROLE:

You will take ownership of the entire data architecture, acting as the most senior individual contributor within Data Engineering. This is a hands-on leadership role focused on technical ownership rather than people management.
Key responsibilities include:

• Designing and owning the company’s data architecture from the ground up
• Building scalable batch and real-time data pipelines
• Developing data ingestion, storage, and transformation frameworks
• Supporting AI and machine learning infrastructure, including vector search systems
• Implementing data quality, monitoring, and observability practices
• Collaborating closely with AI, backend engineering, and product teams
• Optimising performance, scalability, and reliability of large datasets
• Influencing long-term technical strategy and laying foundations for the data function

YOUR SKILLS AND EXPERIENCE:

You will bring strong capability in:

• Python development and building scalable distributed data systems
• Data architecture design and pipeline development
• Batch and streaming data processing
• Relational databases (PostgreSQL or similar)
• NoSQL and modern vector databases (e.g., Qdrant, Milvus, pgvector)

THE BENEFITS:

You will receive a salary of up to £100,000 depending on experience.

HOW TO APPLY:

Please register your interest by sending your CV to Molly Bird via the apply link on this page.

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Research Engineer, Multimodal Datasets

US Remote
$400k + Equity

This is an opportunity to shape how next generation AI systems learn about the world. You will work at the intersection of data, modelling, and experimentation, owning the datasets that underpin cutting edge multimodal models. If you are motivated by high impact research and want to directly influence real world model capability, this role offers uncommon scope and ownership.

The Company
They are a well funded AI research and product organisation focused on advancing multimodal systems beyond traditional language models. Their work centres on building models that can understand and simulate complex environments across video, image, and interactive contexts. With significant recent investment and rapid growth, they operate at the frontier of generative media and real time simulation. The culture is collaborative, research driven, and focused on delivering meaningful technical breakthroughs.

The Role
You will take ownership of the data strategy behind large scale multimodal models, influencing both research direction and real world product capability.

• Design and build large scale multimodal datasets across image and video domains
• Run structured experiments to understand how dataset composition impacts model performance
• Develop and maintain pipelines for synthetic data generation, curation, and quality control
• Define robust evaluation frameworks and benchmarks aligned to real use cases
• Collaborate with research, product, and creative teams to translate goals into data strategies
• Contribute to model training workflows, including pre training and fine tuning

Your Skills and Experience

• Strong commercial experience working with large scale machine learning or foundation models
• Hands on expertise with multimodal data, particularly image or video based systems
• Deep understanding of dataset design, curation, and evaluation in model performance
• Experience working across the full ML lifecycle including training, experimentation, and analysis
• Proficiency in frameworks such as PyTorch or JAX and distributed compute tools
• Evidence of research contribution, open source work, or strong technical projects
• A curiosity driven mindset with a genuine interest in advancing AI capabilities

What They Offer

• Highly competitive compensation with equity participation
• Fully remote working with a globally distributed team
• Significant ownership and influence over core model capabilities
• Opportunity to work on frontier AI challenges with real world impact
• A fast paced, low ego environment focused on innovation and learning

How to Apply
If you are interested in shaping the future of multimodal AI systems, please apply with your CV and relevant project or publication links.

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Senior Data Scientist – START UP – EQUITY

We are working with an exciting start up company who are committed to making affordable, flexible loans for their customers. This will be their first Data Science hire in the company and will have full ownership on ML models across the business.

Required Experience:

• Experience working in Lending, Loans, Insurance or Credit businesses
• Experience building and deploying Credit Risk Data Models
• AWS, Python & SQL experience

Important Information

• 2 days a week in London
• Up to £70K base
• Equity
• No additional benefits

To Apply for this Job Click Here

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Senior Data Engineer (Snowflake | dbt | Fivetran)

Dallas, TX (Hybrid – 4 Days Onsite)

Salary: $140,000-$165,000 Base + Bonus (Flexible)

We’re partnering with a large, well-established enterprise that’s making a significant investment in modernizing its data platform. This is an opportunity to join a newly formed data engineering organization focused on building scalable, cloud-native solutions that will support critical business initiatives across the enterprise.

You’ll be joining early in a long-term transformation, working with modern technologies including Snowflake, dbt, Fivetran, Python, and SQL to build robust data pipelines, optimize data models, and help establish engineering best practices. Whether your expertise is centered around dbt or Fivetran, this team is looking for experienced engineers who enjoy solving complex data challenges in a collaborative environment.

What You’ll Do

• Design, build, and maintain scalable ELT pipelines using modern cloud technologies.
• Develop and optimize data models within Snowflake for analytics and reporting.
• Build and support data ingestion pipelines using Fivetran and transformation workflows using dbt.
• Develop solutions using Python and advanced SQL.
• Partner with analytics, engineering, and business teams to translate requirements into scalable data products.
• Improve data quality, testing, monitoring, and pipeline reliability.
• Contribute to CI/CD processes and Infrastructure as Code initiatives.
• Help define engineering standards and best practices across a growing enterprise data platform.

What We’re Looking For

• 5+ years of Data Engineering experience.
• Strong experience with Snowflake.
• Hands-on experience with dbt and/or Fivetran.
• Advanced SQL and Python skills.
• Experience building production-grade cloud data pipelines.
• Experience with AWS, Azure, or GCP.
• Familiarity with Git, CI/CD, and modern software development practices.

Nice to Have

• Terraform
• Kafka or streaming technologies
• Data modeling and dimensional modeling experience
• Experience with automated testing and data quality frameworks
• Financial services experience (not required)

Why Consider This Opportunity?

• Join a greenfield enterprise data transformation with strong executive sponsorship.
• Work with a modern cloud-native technology stack.
• Small, collaborative engineering team with significant growth planned.
• Opportunity to influence engineering standards and platform direction.
• Long-term career growth with continued investment in learning and development.
• Competitive compensation, bonus, and a stable organization investing heavily in its technology roadmap.

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Position Summary

The Lead Data Solutions Engineer is responsible for designing, developing, implementing, and supporting enterprise-scale data platforms and solutions. This individual will collaborate closely with architects, engineers, analytics teams, business stakeholders, and technology partners to define best practices, establish governance standards, and drive adoption of modern data engineering methodologies.

This role serves as a subject matter expert for enterprise data solutions, providing technical leadership, mentoring team members, and guiding strategic decisions related to data architecture, engineering, and platform optimization.

Key Responsibilities

Data Platform Architecture & Engineering

• Lead the design, implementation, and governance of enterprise ETL/ELT pipelines utilizing modern cloud data technologies.
• Architect and review end-to-end data workflows from source systems through curated, analytics-ready datasets.
• Design scalable data architectures supporting ingestion, transformation, storage, and consumption layers.
• Develop reusable frameworks and patterns that improve maintainability, consistency, and efficiency across data engineering initiatives.

Snowflake & Cloud Data Solutions

• Design andoptimize Snowflake-based data platforms, including:
  • Warehouse sizing and workload management
  • Performance optimization and tuning
  • Data security and access control frameworks
  • Cost management and resource governance
• Establish best practices for enterprise-scale cloud data operations.

Analytics Engineering & Data Modeling

• Develop and govern data transformation frameworks using dbt.
• Create modular and reusable data models across staging, intermediate, and business-layer datasets.
• Implement documentation, testing, lineage tracking, and quality controls.
• Build standards that promote transparency, reliability, and self-service analytics.

Data Pipeline Development

• Design and support highly scalable data pipelines using SQL, Python, and PySpark.
• Build solutions that accommodate batch, streaming, and hybrid processing requirements.
• Oversee ingestion frameworks and ensure reliable movement of data across multiple environments and platforms.

Infrastructure Automation & DevOps

• Implement Infrastructure as Code (IaC) practices using Terraform.
• Automate provisioning and management of data platform resources.
• Design CI/CD processes supporting:
  • Automated deployments
  • Environment promotion strategies
  • Source control and release management
  • Code quality validation and testing

Data Quality & Operational Excellence

• Establish standards for monitoring, observability, and data quality management.
• Ensure data platforms are reliable, scalable, and production-ready.
• Define service-level expectations and operational support processes.
• Drive continuous improvement initiatives focused on platform stability and performance.

Technical Leadership

• Lead architecture reviews, proofs of concept, and technology evaluations.
• Mentor and coach data engineers, providing technical guidance and best practices.
• Facilitate technical discussions and represent the data engineering function in cross-functional meetings.
• Influence enterprise-wide standards, governance models, and architectural direction.

Security, Compliance & Governance

• Partner with security, platform, and compliance teams to implement enterprise data governance requirements.
• Ensure solutions meet security, regulatory, and access-control standards.
• Balance governance objectives with engineering efficiency and delivery goals.

Required Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Engineering, Mathematics, Economics, or a related discipline, or equivalent practical experience.
• 7+ years of experience delivering enterprise-scale data engineering solutions.
• Demonstrated success leading large-scale data platform initiatives in cloud and/or hybrid environments.
• Strong experience building and supporting complex, high-volume data pipelines in production environments.
• Expertise in cloud data warehousing, data modeling, and modern analytics engineering practices.
• Advanced proficiency with SQL and strong hands-on experience with Python and/or PySpark.
• Experience with Snowflake, dbt, Fivetran, Terraform, and modern data ecosystem tools.
• Strong understanding of enterprise data warehousing concepts and architecture patterns.
• Experience designing, developing, testing, and deploying business intelligence and analytics solutions.
• Knowledge of CI/CD, Infrastructure as Code, and software development lifecycle best practices.
• Strong analytical, problem-solving, and systems-thinking capabilities.
• Excellent verbal and written communication skills with the ability to present complex technical concepts to both technical and non-technical audiences.
• Proven ability to lead initiatives, influence stakeholders, and drive outcomes with minimal oversight.
• Strong sense of ownership, accountability, and commitment to continuous improvement.

Preferred Experience

• Experience with AWS and/or Azure cloud environments.
• Exposure to Kafka or event-driven data architectures.
• Experience establishing data governance, metadata, and lineage frameworks.
• Background evaluating and implementing emerging data technologies.
• Experience mentoring engineering teams and contributing to enterprise architecture strategies.

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Senior Data Analyst

London (Hybrid)

Up to £45,000-£50,000

The Opportunity

We’re partnering with a leading B2B media and events business looking for a Senior Data Analyst to help drive smarter decision-making across the organisation.

This is a highly visible role where you’ll work closely with commercial, marketing, editorial, product, finance, and events teams to deliver actionable insights, develop business-critical dashboards, and support strategic growth initiatives. You’ll play a key role in transforming data into measurable business value.

Key Responsibilities

• Design, build, and maintain dashboards for business reporting
• Develop KPI reporting across digital products, events, subscriptions, CRM, and marketing channels
• Analyse audience behaviour, content engagement, campaign performance, and customer journeys
• Deliver actionable insights and recommendations to key stakeholders
• Produce recurring, ad-hoc, post-campaign, and post-event reporting
• Champion data-driven decision-making across the business
• Ensure data accuracy and reporting quality through monitoring and investigation
• Collaborate with stakeholders to define metrics, reporting requirements, and success measures
• Support reporting automation and continuous improvement initiatives
• Contribute to data governance and best-practice standards

What We’re Looking For

• Proven experience as a Data Analyst or Senior Data Analyst
• Strong SQL skills and experience working with large datasets
• Expertise in dashboard creation and self-service reporting
• Experience with BI tools such as Power BI, Looker Studio, or Tableau
• Knowledge of GA4, Google Tag Manager, and CRM platforms
• Strong analytical and problem-solving capabilities
• Ability to communicate complex insights to non-technical stakeholders
• Commercial mindset with a focus on business impact
• Excellent attention to detail and stakeholder management skills
• Experience within media, publishing, events, or subscription-based businesses is advantageous

Ways of Working

• Hybrid working environment
• Cross-functional exposure across multiple business functions
• Opportunity to influence strategic decisions
• Collaborative and data-driven culture
• High level of ownership and autonomy

Benefits

• Competitive salary (£45,000-£50,000)
• Performance-related bonus scheme
• Flexible working arrangements
• 25 days annual leave plus bank holidays
• Additional birthday leave
• Private medical insurance
• Pension scheme
• Enhanced family leave
• Income protection and enhanced sick pay
• Employee referral bonus scheme
• Company summer and Christmas events

How to Apply

If you’re a commercially minded analyst who enjoys turning data into meaningful business insights, we’d love to hear from you.

Apply with your CV or reach out to me!

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Data Engineer

Location: Richardson, TX (Hybrid)

Compensation: $140,000-$160,000 Base + Annual Bonus + Comprehensive Benefits

About the Opportunity

A leading financial services organization is investing heavily in the modernization of its enterprise data platform and is looking for a Senior Data Engineer to join its growing Data Engineering team.

As a Data Engineer, you’ll help shape the future of a cloud-first data ecosystem supporting enterprise analytics, reporting, and data-driven decision making across a large, complex organization. You’ll partner with architects, engineers, and business stakeholders to build scalable, production-grade data solutions while helping establish engineering standards and best practices across the platform.

What You’ll Do

• Design, build, and optimize enterprise-scale ETL/ELT pipelines
• Develop modern cloud data solutions using AWS, Snowflake, dbt, and Fivetran
• Create scalable, reusable data models that power analytics and reporting
• Design high-performance Snowflake architectures with a focus on scalability, security, and cost optimization
• Build robust data transformations using SQL, Python, and PySpark
• Implement Infrastructure as Code using Terraform
• Develop CI/CD pipelines for automated deployment and testing of data assets
• Improve data quality, observability, governance, and operational monitoring
• Partner with engineering, architecture, security, and analytics teams to deliver enterprise data solutions
• Mentor other engineers and help establish engineering standards across the organization

What We’re Looking For

• 4+ years of Data Engineering experience
• Strong experience designing and building enterprise-scale data pipelines
• Hands-on expertise with Snowflake, dbt, and Fivetran
• Experience building cloud-native data platforms in AWS
• Advanced SQL and Python skills (PySpark preferred)
• Experience with Terraform and Infrastructure as Code
• Experience implementing CI/CD for data engineering workflows
• Strong understanding of modern data architecture, data modeling, and analytics engineering
• Excellent communication skills with the ability to collaborate across technical and business teams

Why Join?

• Highly visible role driving enterprise data transformation
• Modern cloud-native technology stack
• Opportunity to influence engineering standards and architecture
• Collaborative, innovation-focused engineering culture
• Competitive compensation, annual bonus, comprehensive benefits, and long-term career growth

To Apply for this Job Click Here

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What You’ll Do

• Evaluate existing machine learning models and identify performance improvement opportunities
• Train, test, deploy, and continuously refine production ML models
• Improve feature engineering, model architectures, prediction accuracy, and optimization performance
• Analyze large-scale datasets containing millions of records across multiple sources
• Design and execute experiments to validate model improvements
• Develop production-quality Python code and collaborate through code reviews and testing practices
• Translate insights from complex datasets into measurable product and business outcomes
• Monitor model effectiveness and evolve solutions as user behavior and market conditions change
• Partner with Product, Engineering, and Data teams to align machine learning initiatives with business objectives

What Success Looks Like

During the first several months, you will:

• Gain a deep understanding of existing machine learning systems and business objectives
• Analyze large and complex datasets to uncover optimization opportunities
• Improve prediction, ranking, recommendation, or optimization models
• Introduce enhanced features, architectures, and model configurations
• Deliver production-ready improvements that positively impact key performance metrics and revenue

Ideal Background

Successful candidates may come from backgrounds such as:

• Senior Machine Learning Engineer
• Applied Machine Learning Engineer
• Data Scientist with strong production ML experience
• Software Engineer specializing in Machine Learning

Experience in any of the following areas is highly valued:

• Advertising technology and optimization
• Ranking and bidding systems
• Recommendation engines
• Personalization systems
• Search and relevance algorithms
• Marketplace optimization
• User value prediction
• Large-scale forecasting and predictive systems

Candidates from consumer technology, marketplaces, digital products, or other large-scale data environments are encouraged to apply.

Required Qualifications

• 5+ years of industry experience in Machine Learning Engineering, Applied Machine Learning, or Data Science
• Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related technical field
• Strong Python programming skills with hands-on experience building ML solutions
• Advanced SQL skills, including complex joins, aggregations, and multi-source analysis
• Experience working with datasets containing millions of records
• Experience building, deploying, and optimizing production machine learning models
• Strong understanding of feature engineering and its impact on model performance
• Experience writing maintainable, testable, production-quality code
• Ability to operate independently and drive technical decisions

Preferred Qualifications

• Experience with optimization, ranking, recommendation, or personalization systems
• Background in advertising technology or digital monetization platforms
• Familiarity with feature stores and modern machine learning workflows
• Experience with cloud platforms and modern data technologies
• Knowledge of large-scale experimentation frameworks and model evaluation methodologies

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CRO Manager

Macclesfield – Hybrid (2-3 Days Per Week)

£50k-£60k

I’m hiring a CRO Manager for one of the UK’s leading customer generation businesses, operating a portfolio of high-traffic digital brands across B2B and B2C markets.

This is a rare opportunity to build an in-house CRO function from scratch, taking ownership of experimentation strategy across multiple brands, products, and customer journeys while helping shape the future of optimisation within the business.

The company

A fast-growing performance marketing and technology business that owns and operates its own digital brands rather than acting as an agency.

Established in 2013, they’ve grown into an international organisation operating across the UK, USA, Canada, Australia, and France, generating high-intent leads through a combination of proprietary technology, data, and digital marketing.

With more than 40 products across multiple acquisition funnels and customer journeys, they have significant traffic volumes and enormous optimisation potential.

The opportunity

After investing in CRO through external consultants for the last two years, the business is now bringing the capability in-house for the first time.

Reporting directly into senior leadership, you’ll have full ownership of:

• The experimentation roadmap
• CRO strategy
• Testing framework and methodology
• Optimisation prioritisation
• Future team growth

This is a genuine greenfield role with strong executive support and a clear opportunity to build a team around you over time.

What you’ll be doing

• Own and develop the CRO roadmap across multiple digital brands
• Design, execute and analyse A/B and multivariate tests
• Build a scalable experimentation framework and testing culture
• Analyse customer behaviour and identify opportunities to improve conversion performance
• Partner with developers to implement experiments and winning variants
• Collaborate with PPC, Marketing, Product and Media Buying teams
• Measure and communicate the commercial impact of optimisation activity
• Prioritise initiatives based on business value and revenue opportunity
• Help establish and grow the company’s internal CRO capability

What they’re looking for

Must-haves

• 5+ years’ experience in Conversion Rate Optimisation
• Proven experience running end-to-end experimentation programmes
• Strong hypothesis generation and test design skills
• Experience withCRO platforms such as:
  • Optimizely
  • VWO
  • Convert.com
  • AB Tasty
  • Similar tools
• Strong understanding of customer journey optimisation
• Experience working on high-traffic websites
• Excellent stakeholder management and communication skills
• Commercial mindset focused on measurable business outcomes

Nice to have

• Lead generation experience
• Agency experience
• Previous mentoring or management experience
• Experience helping build or mature an experimentation function

The team

Initially you’ll operate as an individual contributor with full ownership of experimentation.

You’ll work closely with:

• Marketing
• PPC
• Media Buying
• Product
• Development

The business already has strong development resources in place to support implementation, allowing you to focus on identifying and delivering high-impact opportunities.

Why this role

• Build an internal CRO capability from the ground up
• Own experimentation strategy across multiple brands
• Huge volumes of traffic and optimisation opportunities
• Strong backing from senior leadership
• Clear pathway into team leadership
• Genuine autonomy and ownership from day one
• Exposure across international markets
• Significant commercial impact

Package

• £50,000 – £60,000 salary
• Bonus scheme
• Hybrid working (3 days min per week in Macclesfield)
• Clear progression into leadership
• High levels of ownership and responsibility

Interview process

1. Initial interview with Marketing Manager
2. Practical task and presentation focused on experimentation strategy
3. Final interview with senior leadership

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Lead Decision Scientist (Experimentation)

Hybrid | Brighton | £90,000 Base

We’re partnering with a fast-growing, product-led technology business that is investing heavily in its Data & AI function. As the organisation evolves, they’re looking for a commercially minded Lead Decision Scientist to help shape product strategy through data-driven decision making.

This is an analytics-focused role where you’ll work closely with Product Managers and Engineering teams to identify opportunities, size business impact and influence where the business invests.

The Role

You’ll be responsible for:

• Identifying and solving high-value business problems through data.
• Conducting product and exploratory analysis to uncover opportunities.
• Designing and measuring experiments, including A/B testing.
• Defining success metrics and evaluating product performance.
• Translating analytical insights into clear commercial recommendations.
• Partnering with cross-functional teams to influence product decisions.

What We’re Looking For

• Experience in Product Analytics, Decision Science or Commercial Analytics.
• Strong SQL and analytical problem-solving skills.
• Experience designing and evaluating experiments.
• Excellent stakeholder management and communication skills.
• A commercial mindset with the ability to influence decision making.
• Comfortable working in fast-paced, ambiguous product environments.

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