data & AI
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Data Analyst II – Product Experimentation & Analytics

United States: Fully Remote

Compensation: USD $80,000-$100,000 base + 10% target bonus

Canada: Montreal, QC

Compensation: CAD $75,000-$95,000 base + 10% target bonus

Equity: None

Work Authorization (U.S.): U.S. Citizens and Green Card holders

About the Company

This growing consumer technology organization builds digital products designed to help people better understand and improve their health and wellbeing. The business is entering an important stage of growth, expanding its offering while investing more heavily in experimentation, analytics, and data-informed product development.

You’ll join a small, collaborative environment where Data works directly with Product and Engineering. Analysts are expected to go beyond reporting-asking the right questions, challenging assumptions, and using experimentation and user behavior data to influence what gets built next.

About the Role

The Data Analyst II will become a key analytics partner to the Product organization, with approximately 70% of the role focused on experimentation and 30% on broader product analytics.

This isn’t a role focused on building dashboards and responding to ad hoc requests.

You’ll partner directly with Product Managers to design experiments, determine how success should be measured, analyze results, and translate findings into recommendations that influence product decisions.

The initial priority is improving the quality and reliability of the existing experimentation program. From there, you’ll help scale the volume of testing while establishing stronger experimentation processes and measurement standards.

You’ll also take ownership of the team’s product analytics platform, partnering with Product and Engineering on event tracking, instrumentation, dashboards, and self-service analytics.

Key Responsibilities

• Partner directly with Product Managers throughout the experimentation lifecycle
• Design, measure, and analyze A/B tests and translate results into clear product recommendations
• Improve experimentation methodology, measurement quality, and decision-making
• Help scale a growing experimentation program while maintaining testing quality
• Own product analytics across Mixpanel or a comparable platform
• Define metrics and event-tracking requirements alongside Product and Engineering
• Establish new product events, requirements documentation, validation, and QA
• Build and maintain dashboards that enable Product teams to answer questions independently
• Analyze user behavior, conversion, engagement, and product performance
• Review historical experiments and identify opportunities to improve future testing
• Translate complex analysis into clear insights for technical and non-technical stakeholders

Must Haves

• 2-4 years of Product Analytics, Data Analytics, or similar experience
• Strong hands-on A/B testing and experimentation experience
• Experience owning experiments from initial design through analysis and recommendations
• Experience with Mixpanel, Amplitude, or a comparable product analytics platform
• Strong working knowledge of SQL
• Experience partnering directly with Product Managers
• Understanding of product instrumentation, event tracking, and metric definition
• Direct-to-consumer product experience
• Strong communication and stakeholder management skills
• Ability to turn analysis into clear product recommendations rather than simply presenting results

Nice to Have

• Mobile application analytics experience
• Experience working in a high-experimentation product environment
• Consumer health or digital health experience
• Experience improving or scaling an existing experimentation program
• Experience creating self-service product analytics environments

Why Join

• Become a core analytics partner to Product rather than operating as a reporting resource
• Own experimentation from initial hypothesis through product recommendation
• Help improve and scale an experimentation program at an important stage of growth
• Work directly with Product and Engineering on how user behavior is measured
• Have meaningful influence over product decisions within a small, highly collaborative team
• Work on a consumer-facing digital product where experimentation directly impacts the user experience

To Apply for this Job Click Here

To Apply for this Job Click Here

Private Cloud Architect

Location: Dallas, TX

Work Model: Onsite – 5 days per week

Compensation: $200,000-$210,000 base + bonus + equity

About the Company

This established enterprise organization is making a significant investment in modernizing its infrastructure and building a next-generation private cloud platform.

The goal is to bring public-cloud-style capabilities into the data center-giving engineering teams secure, automated, self-service access to compute, storage, networking, and platform services while creating a consistent experience across private and public cloud environments.

The engineering culture values technical ownership, automation, strong architectural judgment, and leaders who remain close to the technology while defining long-term platform direction.

About the Role

This is a senior, hands-on architecture role responsible for defining and evolving an enterprise private cloud platform.

You’ll lead the transition from traditional data center infrastructure toward a modern, software-defined platform built around Kubernetes, Infrastructure as Code, automation, APIs, and self-service capabilities.

A major part of the mandate is creating an internal cloud experience that gives developers the speed and usability they expect from public cloud while maintaining the control, performance, security, and reliability required within an enterprise data center.

You’ll also shape how private infrastructure integrates with AWS, Azure, and GCP to create a cohesive hybrid cloud architecture.

Key Responsibilities

• Define the architecture and long-term strategy for enterprise private cloud infrastructure
• Design cloud-native platforms across compute, storage, networking, and shared platform services
• Build and evolve Kubernetes-based environments using OpenShift, Rancher, or comparable technologies
• Develop self-service infrastructure capabilities through APIs, automation, and developer-friendly interfaces
• Design hybrid architectures connecting private infrastructure with public cloud environments
• Establish Infrastructure as Code and automation standards using Terraform or similar technologies
• Architect highly available and resilient distributed infrastructure at enterprise scale
• Modernize legacy infrastructure and transition workloads toward cloud-native architectures
• Design infrastructure capable of supporting high-performance computing and GPU-intensive workloads
• Partner with networking, security, SRE, and application engineering teams on end-to-end platform architecture
• Establish platform governance, security, observability, and operational standards
• Provide architectural leadership while remaining technically close to implementation

Must Haves

• 8+ years of infrastructure, cloud, platform engineering, or architecture experience
• Deep experience designing private cloud or large-scale data center infrastructure
• Strong Kubernetes experience, ideally including OpenShift or Rancher
• Experience designing hybrid architectures spanning on-premises infrastructure and AWS, Azure, or GCP
• Strong Infrastructure as Code and automation experience, including Terraform
• Experience designing highly available, scalable distributed systems
• Strong understanding of compute, storage, networking, and platform infrastructure
• Experience with CI/CD, GitOps, and infrastructure automation
• Ability to define architecture while remaining technically hands-on
• Experience modernizing established enterprise infrastructure rather than exclusively working in public cloud

Nice to Have

• Internal developer platforms, private cloud portals, or self-service infrastructure
• Advanced data center networking, including L2/L3 architecture and segmentation
• EVPN/VXLAN or software-defined networking
• Kafka, Spark, Flink, or similar distributed data technologies
• GPU or HPC infrastructure
• Grafana, Prometheus, and modern observability platforms
• IAM, identity integration, or Zero Trust architecture
• Microservices architecture
• Experience operating across multiple public cloud providers

Why Join

• Architect a private cloud platform rather than simply maintain traditional infrastructure
• Build an internal cloud experience that brings automation and self-service capabilities into the enterprise data center
• Own major architectural decisions across Kubernetes, compute, storage, networking, automation, and hybrid cloud
• Lead the modernization of legacy infrastructure into scalable cloud-native platforms
• Remain technically hands-on while having significant influence over long-term platform strategy
• Work on complex infrastructure challenges including hybrid cloud, distributed systems, GPU/HPC workloads, and advanced networking

To Apply for this Job Click Here

To Apply for this Job Click Here

Lead Data Scientist

$140,000-$150,000 + 10% bonus

Overview

A growing organisation is seeking an experienced Lead Data Scientist to drive strategic analytics initiatives across customer experience, operational efficiency, asset performance, and cost optimisation. This highly visible role partners closely with senior business leaders to identify challenges, develop data-driven solutions, and influence decision-making through advanced analytics and predictive modelling.
The ideal candidate combines deep technical expertise with strong business acumen, excels at communicating complex concepts to non-technical audiences, and has a proven track record of leading projects from concept through implementation with minimal supervision.

Key Responsibilities

Project Leadership & Stakeholder Management

• Build trusted relationships with senior stakeholders, including director- and executive-level leaders.
• Independently lead projects from problem definition through deployment and performance monitoring.
• Facilitate intake sessions, define project scope, estimate effort, manage priorities, and communicate progress effectively.
• Mentor and guide junior analysts and data scientists on methodology, project structure, and technical execution.
• Present findings and recommendations to leadership teams, including executive audiences.

Advanced Analytics & Data Science

• Develop and deploy predictive models using machine learning techniques such as gradient boosting, ensemble methods, decision trees, and other supervised and unsupervised learning approaches.
• Design segmentation frameworks using clustering and classification techniques.
• Conduct statistical analysis, model validation, back-testing, and performance measurement to ensure reliability and business value.
• Identify patterns, root causes, and opportunities through large-scale data analysis.
• Develop innovative analytical approaches to improve insight generation and operational effectiveness.
• Support business decision-making through forecasting, scoring models, optimisation techniques, and operational analytics.

Data Management & Process Improvement

• Gather, reconcile, clean, validate, and integrate data from multiple internal and external sources.
• Establish data quality standards and controls to improve accuracy and consistency.
• Design and implement processes that reduce risk, improve efficiency, and create measurable business value.
• Monitor and assess the ongoing performance of implemented analytical solutions.

Executive Communication

• Translate complex analytical findings into actionable business recommendations.
• Develop compelling executive presentations and data-driven narratives that influence organisational strategy and operational improvements.

Required Qualifications

• Bachelor’s degree in a quantitative field such as Mathematics, Statistics, Engineering, Economics, Computer Science, or a related discipline.
• 10+ years of experience in data science, advanced analytics, predictive modelling, risk analytics, or a related quantitative function.
• 3+ years of hands-on Python experience building machine learning, forecasting, regression, classification, and segmentation models.
• 3+ years of advanced SQL experience, including optimisation of complex queries across large datasets.
• Strong expertise in statistical methods, probability theory, experimental design, predictive analytics, sampling techniques, and model evaluation.
• Demonstrated experience analysing large structured and unstructured datasets.
• Experience presenting analytical insights to executive audiences and influencing strategic decisions.
• Ability to communicate complex technical concepts to business stakeholders with varying levels of analytical expertise.
• Strong project management, prioritisation, and multitasking skills.
• Proven ability to work independently in a fast-paced, evolving environment.
• Experience sourcing, validating, and integrating data from multiple systems and platforms.

Preferred Qualifications

• Master’s degree in a quantitative discipline.
• Experience in risk management, portfolio analytics, financial modelling, or asset performance analysis.
• Experience using consumer, credit, demographic, or third-party external datasets.
• Prior experience developing scoring models, predictive risk models, or decision-support frameworks.
• Experience within highly regulated industries where model governance, validation, and audit requirements are critical.
• Familiarity with model risk management frameworks and third-party model review processes.
• Experience working with cloud-based data and analytics environments, including object storage and large-scale compute platforms.
• Experience with modern data warehouse technologies.

To Apply for this Job Click Here

To Apply for this Job Click Here

Lead Data Scientist

$140,000-$150,000 + 10% bonus

Overview

A growing organisation is seeking an experienced Lead Data Scientist to drive strategic analytics initiatives across customer experience, operational efficiency, asset performance, and cost optimisation. This highly visible role partners closely with senior business leaders to identify challenges, develop data-driven solutions, and influence decision-making through advanced analytics and predictive modelling.
The ideal candidate combines deep technical expertise with strong business acumen, excels at communicating complex concepts to non-technical audiences, and has a proven track record of leading projects from concept through implementation with minimal supervision.

Key Responsibilities

Project Leadership & Stakeholder Management

• Build trusted relationships with senior stakeholders, including director- and executive-level leaders.
• Independently lead projects from problem definition through deployment and performance monitoring.
• Facilitate intake sessions, define project scope, estimate effort, manage priorities, and communicate progress effectively.
• Mentor and guide junior analysts and data scientists on methodology, project structure, and technical execution.
• Present findings and recommendations to leadership teams, including executive audiences.

Advanced Analytics & Data Science

• Develop and deploy predictive models using machine learning techniques such as gradient boosting, ensemble methods, decision trees, and other supervised and unsupervised learning approaches.
• Design segmentation frameworks using clustering and classification techniques.
• Conduct statistical analysis, model validation, back-testing, and performance measurement to ensure reliability and business value.
• Identify patterns, root causes, and opportunities through large-scale data analysis.
• Develop innovative analytical approaches to improve insight generation and operational effectiveness.
• Support business decision-making through forecasting, scoring models, optimisation techniques, and operational analytics.

Data Management & Process Improvement

• Gather, reconcile, clean, validate, and integrate data from multiple internal and external sources.
• Establish data quality standards and controls to improve accuracy and consistency.
• Design and implement processes that reduce risk, improve efficiency, and create measurable business value.
• Monitor and assess the ongoing performance of implemented analytical solutions.

Executive Communication

• Translate complex analytical findings into actionable business recommendations.
• Develop compelling executive presentations and data-driven narratives that influence organisational strategy and operational improvements.

Required Qualifications

• Bachelor’s degree in a quantitative field such as Mathematics, Statistics, Engineering, Economics, Computer Science, or a related discipline.
• 10+ years of experience in data science, advanced analytics, predictive modelling, risk analytics, or a related quantitative function.
• 3+ years of hands-on Python experience building machine learning, forecasting, regression, classification, and segmentation models.
• 3+ years of advanced SQL experience, including optimisation of complex queries across large datasets.
• Strong expertise in statistical methods, probability theory, experimental design, predictive analytics, sampling techniques, and model evaluation.
• Demonstrated experience analysing large structured and unstructured datasets.
• Experience presenting analytical insights to executive audiences and influencing strategic decisions.
• Ability to communicate complex technical concepts to business stakeholders with varying levels of analytical expertise.
• Strong project management, prioritisation, and multitasking skills.
• Proven ability to work independently in a fast-paced, evolving environment.
• Experience sourcing, validating, and integrating data from multiple systems and platforms.

Preferred Qualifications

• Master’s degree in a quantitative discipline.
• Experience in risk management, portfolio analytics, financial modelling, or asset performance analysis.
• Experience using consumer, credit, demographic, or third-party external datasets.
• Prior experience developing scoring models, predictive risk models, or decision-support frameworks.
• Experience within highly regulated industries where model governance, validation, and audit requirements are critical.
• Familiarity with model risk management frameworks and third-party model review processes.
• Experience working with cloud-based data and analytics environments, including object storage and large-scale compute platforms.
• Experience with modern data warehouse technologies.

To Apply for this Job Click Here

To Apply for this Job Click Here

Lead Data Scientist

$140,000-$150,000 + 10% bonus

Overview

A growing organisation is seeking an experienced Lead Data Scientist to drive strategic analytics initiatives across customer experience, operational efficiency, asset performance, and cost optimisation. This highly visible role partners closely with senior business leaders to identify challenges, develop data-driven solutions, and influence decision-making through advanced analytics and predictive modelling.
The ideal candidate combines deep technical expertise with strong business acumen, excels at communicating complex concepts to non-technical audiences, and has a proven track record of leading projects from concept through implementation with minimal supervision.

Key Responsibilities

Project Leadership & Stakeholder Management

• Build trusted relationships with senior stakeholders, including director- and executive-level leaders.
• Independently lead projects from problem definition through deployment and performance monitoring.
• Facilitate intake sessions, define project scope, estimate effort, manage priorities, and communicate progress effectively.
• Mentor and guide junior analysts and data scientists on methodology, project structure, and technical execution.
• Present findings and recommendations to leadership teams, including executive audiences.

Advanced Analytics & Data Science

• Develop and deploy predictive models using machine learning techniques such as gradient boosting, ensemble methods, decision trees, and other supervised and unsupervised learning approaches.
• Design segmentation frameworks using clustering and classification techniques.
• Conduct statistical analysis, model validation, back-testing, and performance measurement to ensure reliability and business value.
• Identify patterns, root causes, and opportunities through large-scale data analysis.
• Develop innovative analytical approaches to improve insight generation and operational effectiveness.
• Support business decision-making through forecasting, scoring models, optimisation techniques, and operational analytics.

Data Management & Process Improvement

• Gather, reconcile, clean, validate, and integrate data from multiple internal and external sources.
• Establish data quality standards and controls to improve accuracy and consistency.
• Design and implement processes that reduce risk, improve efficiency, and create measurable business value.
• Monitor and assess the ongoing performance of implemented analytical solutions.

Executive Communication

• Translate complex analytical findings into actionable business recommendations.
• Develop compelling executive presentations and data-driven narratives that influence organisational strategy and operational improvements.

Required Qualifications

• Bachelor’s degree in a quantitative field such as Mathematics, Statistics, Engineering, Economics, Computer Science, or a related discipline.
• 10+ years of experience in data science, advanced analytics, predictive modelling, risk analytics, or a related quantitative function.
• 3+ years of hands-on Python experience building machine learning, forecasting, regression, classification, and segmentation models.
• 3+ years of advanced SQL experience, including optimisation of complex queries across large datasets.
• Strong expertise in statistical methods, probability theory, experimental design, predictive analytics, sampling techniques, and model evaluation.
• Demonstrated experience analysing large structured and unstructured datasets.
• Experience presenting analytical insights to executive audiences and influencing strategic decisions.
• Ability to communicate complex technical concepts to business stakeholders with varying levels of analytical expertise.
• Strong project management, prioritisation, and multitasking skills.
• Proven ability to work independently in a fast-paced, evolving environment.
• Experience sourcing, validating, and integrating data from multiple systems and platforms.

Preferred Qualifications

• Master’s degree in a quantitative discipline.
• Experience in risk management, portfolio analytics, financial modelling, or asset performance analysis.
• Experience using consumer, credit, demographic, or third-party external datasets.
• Prior experience developing scoring models, predictive risk models, or decision-support frameworks.
• Experience within highly regulated industries where model governance, validation, and audit requirements are critical.
• Familiarity with model risk management frameworks and third-party model review processes.
• Experience working with cloud-based data and analytics environments, including object storage and large-scale compute platforms.
• Experience with modern data warehouse technologies.

To Apply for this Job Click Here

To Apply for this Job Click Here

Lead Data Engineer

Up to £85,000

Holborn, London (4 days a week in office)

This is an opportunity to take ownership of a Data Engineering function at a high-growth AI-driven SaaS business. Working directly with senior technology leadership, you will combine hands-on engineering with team leadership, helping to shape the technical direction, standards and future growth of the function.

THE COMPANY

They are a rapidly scaling SaaS organisation that helps businesses unlock greater value from their data through advanced analytics and AI-powered products. Their technology supports enterprise clients across a range of sectors, delivering actionable insights that improve decision-making and commercial performance.

THE ROLE

As a Lead Data Engineer, you will be responsible for leading Data Engineering whilst remaining heavily involved in technical delivery.

Specifically, you can expect to be involved in the following:

• Building and developing the Data Engineering function, including processes, standards and best practices
• Leading, mentoring and managing a team of Data Engineers
• Designing and delivering scalable ETL and ELT pipelines across cloud environments
• Owning data modelling, architecture and platform design decisions
• Collaborating with Product, Data Science, Platform and Client Success teams
• Driving improvements across CI/CD, DevOps and engineering workflows
• Working with clients and stakeholders to understand data challenges and deliver value-driven solutions

SKILLS AND EXPERIENCE

The successful Lead Data Engineer will have the following skills and experience:

• Previous experience leading or managing a Data Engineering team
• Strong commercial experience with SQL and Python
• Expertise in building scalable ETL and ELT pipelines
• Strong understanding of data modelling and modern data architecture principles
• Experience working with cloud platforms such as Azure, AWS or GCP
• Knowledge of Databricks, Azure Data Factory, Microsoft Fabric or similar modern data platforms
• Experience with Git, CI/CD and DevOps best practices
• Strong communication skills with the ability to engage technical and non-technical stakeholders
• Experience in consulting, client-facing or project-led environments would be advantageous

BENEFITS

The successful Lead Data Engineer will receive the following benefits:

• Salary up to £85,000 – depending on experience

HOW TO APPLY

Please register your interest by sending your resume to Majid Latif via the Apply link on this page.

To Apply for this Job Click Here

To Apply for this Job Click Here

Azure Cloud Engineer

£40,000 – £50,000

Abingdon, Oxfordshire (1 day a week in office)

Looking to take ownership of real Azure infrastructure while broadening your exposure to cloud architecture, AI initiatives, and large-scale transformation projects? This is an opportunity to join a growing cloud team where you’ll have a direct impact on both internal platforms and client-facing technology programmes.

THE COMPANY

This consultancy-led organisation delivers technology, cloud, and transformation solutions across a diverse portfolio of public and private sector clients. They are continuing to invest heavily in cloud and AI capabilities and are growing their internal cloud function to support increasing demand. Operating within a fully cloud-native Microsoft Azure environment, the team is responsible for all cloud infrastructure, security, governance, and platform services across the business. You’ll join a collaborative technology team where innovation, practical problem-solving, and continuous improvement are highly valued.

THE ROLE

As an Azure Cloud Engineer, you will support the design, delivery, and ongoing management of cloud infrastructure while working closely with consultants and programme teams across the business.

Specifically, you can expect to be involved in the following:

• Building, supporting, and optimising Microsoft Azure environments
• Managing cloud resources including Virtual Machines, SQL Servers, Web Apps, and containerised applications
• Supporting Azure DevOps and GitHub-based development and deployment processes
• Creating and maintaining CI/CD pipelines
• Assisting with cloud architecture and infrastructure design discussions
• Advising stakeholders on cloud hosting approaches and infrastructure best practices
• Supporting cloud cost optimisation and operational efficiency across the estate

SKILLS AND EXPERIENCE

The successful Azure Cloud Engineer will have the following skills and experience:

• Commercial experience working within Microsoft Azure environments
• Experience deploying and supporting cloud infrastructure end-to-end
• Knowledge of Azure services including compute, networking, storage, and identity management
• Experience with Azure DevOps and/or GitHub
• Experience building and supporting CI/CD pipelines
• Understanding of cloud security, governance, and compliance principles
• Strong stakeholder communication skills and the ability to work with both technical and non-technical teams

BENEFITS

The successful Azure Cloud Engineer will receive the following benefits:

• Salary between £40,000 – £50,000 – depending on experience

HOW TO APPLY

Please register your interest by sending your resume to Majid Latif via the Apply link on this page.

To Apply for this Job Click Here