Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Growth Data Scientist/Analyst

Crypto.com
City of London
2 days ago
Create job alert

We are seeking a dynamic Growth Data Scientist/Analyst to join our Growth team. The successful candidate will be instrumental in leveraging data to drive strategic decisions, optimize growth initiatives, and enhance user acquisition strategies.

Responsibilties
  • Data Analysis and Visualization
  • Design, develop, and maintain interactive dashboards in Tableau to support both recurring and ad-hoc reporting needs across various growth functions and leadership teams, enabling real-time performance tracking and insights.
  • Write and optimize SQL queries to analyze large-scale datasets, supporting initiatives like user acquisition optimization, campaign performance evaluation, and customer lifecycle management to drive business growth.
  • Data Operations and Engineering
  • Partner with cross-functional teams—including growth, product, data engineering, and external vendors—to improve data infrastructure, ensuring accurate, scalable, and efficient data pipelines that support business goals.
  • Streamline and automate recurring data workflows and processes, manage SQL automation and job scheduling, and maintain thorough documentation to enhance team productivity and data reliability.
  • Advanced Data Analysis and Modeling
  • Develop advanced analytical models to inform marketing strategies, including predictive analytics and marketing mix modeling, providing actionable insights for campaign planning and optimization.
  • Leverage statistical techniques and business intelligence tools to uncover trends, patterns, and opportunities that inform strategic growth decisions.
  • Project Management and Problem Solving
  • Collaborate closely with cross-functional stakeholders to implement data-driven solutions and support end-to-end project delivery, ensuring alignment with business objectives and timelines.
  • Stay proactive in professional development by exploring emerging tools and methodologies in data science and analytics, continuously enhancing analytical capabilities and industry knowledge.
Requirements
  • Bachelor’s degree in a quantitative field such as Computer Science, Statistics, Engineering, Information Systems, or related fields.
  • 2+ years of experience in data analysis or a related field. Experience in the Crypto and Technology industry is a plus.
  • Proficiency in SQL, Databricks, and Tableau for processing, analyzing, and visualizing large datasets.
  • Experience with statistical software (e.g., R, Python) and libraries for managing, manipulating, and analyzing data.
  • Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
  • Adept at querying, report writing, and presenting findings.
  • Understanding of digital marketing concepts, such as user acquisition (organic, non-organic, partnerships, etc.), campaign management, and customer lifecycle management.
  • Familiarity with tools like AppsFlyer, Google Tag Manager, Google Analytics, and SensorTower.
  • Strong communication skills to effectively convey complex data insights to non-technical stakeholders and to translate business needs into technical and data requirements.
  • Ability to thrive in a fast-paced environment, manage multiple projects, and adapt to shifting priorities.


#J-18808-Ljbffr

Related Jobs

View all jobs

Product Data Scientist/Analyst

Commercial Data Analyst / Scientist

Commercial Data Analyst / Scientist

Baseball Analyst/Data Scientist

Data Scientist - Music Tech

Mid-level Data Scientist - Applied AI team

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.

Why the UK Could Be the World’s Next Machine Learning Jobs Hub

Machine learning (ML) is becoming essential to industries across the globe—from finance and healthcare to retail, logistics, defence, and the public sector. Its ability to uncover patterns in data, make predictions, drive automation, and increase operational efficiency has made it one of the most in-demand skill sets in the technology world. In the UK, machine learning roles—from engineers to researchers, product managers to analysts—are increasingly central to innovation. Universities are expanding ML programmes, enterprises are scaling ML deployments, and startups are offering applied ML solutions. All signs point toward a surging need for professionals skilled in modelling, algorithms, data pipelines, and AI systems. This article explores why the United Kingdom is exceptionally well positioned to become a global machine learning jobs hub. It examines the current landscape, strengths, career paths, sector-specific demand, challenges, and what must happen for this vision to become reality.