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- Tasks: Analyse large datasets and create bespoke reports to deliver insights for clients.
- Company: Join a rapidly growing Data Science Consulting Team in London/Reading.
- Benefits: Enjoy 29 days of annual leave, competitive salary, and professional development opportunities.
- Why this job: Make an impact by solving real-world problems with data and advanced algorithms.
- Qualifications: 2-4 years in Data Science, strong skills in SQL, Python, and data analytics.
- Other info: Collaborate with global teams and explore exciting projects in the media industry.
The predicted salary is between 35000 - 42000 £ per year.
We are looking for a Data Scientist to join the Data Science Consulting Team based in Reading/London. This new role is responsible for analysing extremely large datasets, creating bespoke client reports, exploring new datasets and building new algorithms to deliver services to clients.
Key Responsibilities
- Explore and extract data from multiple sources and interrogate this data to create meaningful insights.
- Scope and define the approach to typical projects that the Data Science Consulting Team works on.
- Research, develop, and test solutions to problems that use both supervised and unsupervised learning models.
- Discuss technical and analytical aspects of your work with clients.
- Maintain and improve our machine learning pipelines, processes and products.
- Use tools and languages such as Python, SQL and Tableau for reporting and analysis on our AWS data platform.
- Work with our India‑based Data Engineering team and our Sales and Market Research Teams in the US and UK.
- Have knowledge of a broader set of techniques available for each type of ML problem, typically with deep expertise in a couple of areas (e.g. forecasting, segmentation).
- Critically think about what features are required to address a client business problem, and transform the data to achieve this.
- Be confidently relied upon to create models that are robust and do not suffer from issues such as multicollinearity, overfitting, or data leakage.
- Have knowledge of advanced machine‑learning algorithms such as random forest, gradient boosting and support vector machines.
- Experience in feature engineering and selection techniques.
- Understanding of model evaluation metrics and cross‑validation techniques.
Requirements
- 2‑4 years’ experience working within the Data Science domain.
- Proven experience managing Data Science projects independently.
- Desire to understand the why and dig into data to understand what makes people tick.
- Bachelor’s degree in Applied Mathematics, Statistics, Economics, Psychology, Sociology, Physics, Engineering, Computer Science or related field (Master’s or higher is a plus).
- Solid data analytics skills; proven proficiency with SQL, Python & Pandas is a must.
- Ability to understand business problems, draw conclusions from data and recommend actions on how best to solve these problems.
- Strong communication skills and ability to document requirements and work with other team members.
- Appreciation for general quantitative research techniques would be beneficial but not required.
- Experience with TV viewing data, the TV industry and/or Media Industry experience is a plus; genuine interest is sufficient; curiosity about data and enjoyment of building visualisations that clearly articulate insight is expected.
Location
London – London / Reading, UK
Benefits
Generous annual leave of 29 days, PLUS
Data Scientist I in London employer: MarketCast
Contact Detail:
MarketCast Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist I in London
✨Tip Number 1
Network like a pro! Reach out to current Data Scientists on LinkedIn or at meetups. Ask them about their experiences and any tips they might have for landing a role in the team. Personal connections can make all the difference!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, especially those using Python, SQL, and machine learning techniques. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common data science problems and algorithms. Be ready to discuss how you've tackled similar challenges in the past. We want to see your critical thinking and problem-solving skills in action!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows your genuine interest in joining our awesome Data Science Consulting Team!
We think you need these skills to ace Data Scientist I in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight your experience with Python, SQL, and any machine learning projects you've worked on. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how you can contribute to our team. Don't forget to mention any relevant projects or experiences that showcase your analytical skills.
Showcase Your Projects: If you've worked on any interesting data science projects, make sure to include them in your application. We love seeing real-world applications of your skills, so share your successes and what you learned along the way!
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you'll be able to keep track of your application status. Plus, we love seeing candidates who take the initiative!
How to prepare for a job interview at MarketCast
✨Know Your Data Inside Out
Before the interview, dive deep into the datasets you might be working with. Familiarise yourself with common data sources and think about how you would extract insights from them. This will show your potential employer that you're not just a number cruncher but someone who can truly understand and interpret data.
✨Brush Up on Your Algorithms
Make sure you’re well-versed in both supervised and unsupervised learning models. Be ready to discuss specific algorithms like random forests or gradient boosting, and how you've applied them in past projects. This will demonstrate your technical expertise and problem-solving skills.
✨Communicate Clearly
Strong communication is key in this role, especially when discussing technical aspects with clients. Practice explaining complex concepts in simple terms. You might even want to prepare a few examples of how you've successfully communicated insights in previous roles.
✨Show Your Curiosity
Employers love candidates who are genuinely curious about data. Prepare to discuss what intrigues you about data science and how you approach problem-solving. Share any personal projects or interests related to data, as this can set you apart from other candidates.