Growth Data Scientist/ Analyst

Crypto.com
London
1 day 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.

Responsibilities

Develop and maintain acquisition and engagement influencer/affiliate, organic, VIP, paid acquisition etc.) dashboards to monitor user growth and campaign effectiveness. Assist in building predictive models to guide strategic decisions on acquisition and engagement, encompassing time series, predictive analytics, and recommender systems. Analyze data to derive actionable insights that drive business decisions and performance improvements. Automate repetitive tasks and data processes to enhance team efficiency. Collaborate with cross-functional teams to support data-driven decisions and project implementations. Engage in continuous learning to stay ahead of industry trends and leverage new tools and techniques in data analysis.

Requirements

Bachelor’s degree in a quantitative field such as Statistics, Computer Science, Engineering, or related fields. Up to 3 years of experience in data analysis or a related field. Experience in the crypto industry is a plus. Familiarity with User Acquisition (UA) and/or Customer Relationship Management (CRM) concepts is advantageous. Proficiency in SQL and familiarity with data visualization tools like Tableau. Experience with statistical software 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 queries, report writing, and presenting findings. Knowledge of acquisition campaign platforms and tools such as Appsflyer, SensorTower, or similar platforms. Excellent verbal and written communication skills.

Related Jobs

View all jobs

Data Analytics Manager

Senior Data Scientist

Lead Product Analyst - AML Handling

Senior Data Engineer

Senior Data Engineer

Machine Learning & Data Scientist

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

AI vs. Data Science vs. Machine Learning Jobs: Which Path Should You Choose?

In recent years, the fields of Artificial Intelligence (AI), Data Science, and Machine Learning (ML) have experienced explosive growth. Spurred by the increase in data availability, advances in computing power, and the demand for intelligent decision-making, organisations of all sizes are investing heavily in these areas. If you’ve been exploring AI jobs on www.artificialintelligencejobs.co.uk, you’ve likely noticed that employers use terms like “AI,” “Data Science,” and “Machine Learning”—often interchangeably. While they are closely related, there are nuanced differences between these fields. Understanding these distinctions is key if you’re trying to decide which path suits you best. This comprehensive guide will help you differentiate among AI, Data Science, and Machine Learning. We will discuss the key skills for each, typical job roles, salary ranges, and provide real-world examples of professionals working in these fields. By the end, you should have a clearer idea of where your strengths and passions might fit, helping you take the next step towards securing your ideal role in the world of data-driven innovation.

AI Programming Languages for Job Seekers: Which Should You Learn First to Launch Your AI Career?

Artificial Intelligence (AI) is no longer confined to academic research; it now sits at the core of countless modern industries. From healthcare diagnostics powered by machine learning to autonomous driving and natural language processing, organisations are investing heavily in AI capabilities. This surge in AI adoption has created a thriving job market for talented professionals—data scientists, machine learning engineers, AI researchers, and more. Yet if you’re aiming to break into this fast-growing field, one of the first questions you’ll ask is, “Which AI programming language should I learn first?” Given the array of options available—Python, R, Java, C++, Julia, among others—understanding the strengths, community support, and industry relevance of each is crucial. In this extensive guide, tailored for www.artificialintelligencejobs.co.uk, we’ll explore the top AI programming languages that can help you stand out to employers, accelerate your learning curve, and equip you with the skills to succeed in a competitive job market. By addressing both beginners and experienced programmers, we aim to provide actionable insights to help you choose the right language, master essential tools, and build a compelling career in AI.

UK Visa & Work Permits Explained: Your Essential Guide for International AI Talent

The United Kingdom has long been a hub of innovation, drawing some of the world’s brightest minds to its shores. In recent years, the country’s thriving technology ecosystem has been propelled by advances in Artificial Intelligence (AI), Machine Learning (ML), Robotics, Data Science, and related fields. From deep-tech start-ups in Silicon Roundabout to established global powerhouses, the UK remains at the forefront of AI research and development. Yet, for international AI professionals hoping to contribute to the UK’s tech growth, one of the most challenging hurdles can be understanding the visa and work permit landscape. The UK immigration system has its unique nuances, and it can be overwhelming to decide which route is best suited for your career aspirations. This comprehensive guide will help you navigate the main visa and work permit options for AI professionals, provide insight into the eligibility criteria, and offer practical tips on securing your dream role in the British AI sector.