Data Analyst Intern

Pimlico
9 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst - Leakage

Research Data Analyst

Data Analyst

Data Analyst

Company Description

AnxietEase is a dynamic consulting group dedicated to bridging the gap between education and industry. We provide hands-on training programs that equip aspiring professionals with real-world skills, mentorship, and exposure to industry projects, empowering them to thrive in today’s competitive business landscape.

Role Description

This is a part-time remote internship role for a Data Analyst Intern at AnxietEase in London Area, United Kingdom. The Data Analyst Intern will assist in gathering, analysing, and interpreting data to support decision-making processes across various business functions.

Qualifications



Strong analytical and problem-solving skills

*

Proficiency in data analysis tools (Excel, SQL, Power BI, etc.)

*

Knowledge of data visualization techniques and tools

*

Understanding of business processes and decision-making

*

Attention to detail and accuracy

*

Ability to gather, clean, and interpret data sets

*

Strong communication skills

*

Currently pursuing or completed a degree in Data Science, Computer Science, Business Analytics, or a related field

What You’ll Gain

*

Practical Experience: Work on real-world data analysis projects for AnxietEase and multinational collaborations.

*

Mentorship: Receive personalized guidance and feedback from experienced data analysts and mentors.

*

Certifications: Earn up to four certifications, including internship completion and excellence awards.

*

Networking Opportunities: Connect with industry experts and peers.

*

Flexibility: Fully remote program with a customizable schedule to balance your commitments.

Your Role

As a Data Analyst Intern, you will:

*

Assist in collecting, cleaning, and organizing large datasets from various business functions.

*

Analyze data to identify trends, patterns, and insights that support business decisions.

*

Create data visualizations and dashboards to present findings effectively.

*

Collaborate with cross-functional teams to provide data-driven recommendations.

*

Participate in weekly review sessions to improve your skills and understanding of data analysis in a business context.

Program Highlights

*

Duration: 4 weeks

*

Schedule: Flexible

*

Mode: 100% remote

Eligibility

*

Open to undergraduates, recent graduates, or professionals seeking to pivot into data analytics.

*

Strong analytical, problem-solving, and communication skills are preferred.

Application Process

*

Submit your CV and answer assessment questions designed to evaluate your potential and alignment with the program.

*

Participate in a competency assessment.

*

Upon successful evaluation, wait for the decision

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.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.