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- Tasks: Join our advanced analytics team as a Data Scientist, focusing on Marketing Mix Modeling and causal inference.
- Company: We're a fast-paced, data-driven company that values innovation and expertise.
- Benefits: Enjoy a competitive day rate of £480, hybrid work, and potential for contract extension.
- Why this job: This role offers the chance to impact decisions with data while working in a dynamic environment.
- Qualifications: Must have proven experience in MMM and strong communication skills to convey insights effectively.
- Other info: Work 2 days a week in Leicester; initial contract is 3 months with extension possibilities.
The predicted salary is between 57600 - 57600 £ per year.
We're partnering with a highly data-literate, fast-paced company seeking a skilled Contract Data Scientist to join their advanced analytics team. If you thrive in environments where data drives every decision and you bring strong communication skills to match your technical expertise, this one's for you.
Tech Stack:
- Databricks
- SQL
- Python
- PySpark
- Robyn
- Meridian / Light MMM
Nice to Have:
- Dashboarding experience
- PyMC
Requirements:
- Proven Marketing Mix Modeling (MMM) experience
- Solid grasp of causal inference techniques
- Ability to clearly explain complex models and insights to non-technical stakeholders
- Comfortable working in a high-autonomy, fast-delivery environment
Details:
- Day Rate: £480/day
- Outside IR35
- Hybrid: 2 days/week in Leicester
- Duration: Initial 3 months with strong potential for extension
Contact Detail:
Career Wallet Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Familiarise yourself with the specific tools mentioned in the job description, such as Databricks and PySpark. Having hands-on experience or projects showcasing your skills with these technologies can set you apart from other candidates.
✨Tip Number 2
Prepare to discuss your experience with Marketing Mix Modelling (MMM) and causal inference techniques in detail. Be ready to share examples of how you've applied these methods in previous roles, as this will demonstrate your expertise and relevance to the position.
✨Tip Number 3
Since strong communication skills are essential for this role, practice explaining complex data concepts in simple terms. You might want to simulate discussions with non-technical stakeholders to refine your ability to convey insights effectively.
✨Tip Number 4
Research the company’s culture and values to understand their fast-paced environment better. Tailor your approach during interviews to reflect your adaptability and readiness to thrive in a high-autonomy setting, which is crucial for this role.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Marketing Mix Modelling (MMM) and causal inference techniques. Use specific examples to demonstrate your skills in these areas, as well as your proficiency in the required tech stack like SQL, Python, and Databricks.
Craft a Compelling Cover Letter: In your cover letter, emphasise your strong communication skills and ability to explain complex models to non-technical stakeholders. Mention your experience in fast-paced environments and how you can contribute to the advanced analytics team.
Showcase Relevant Projects: If you have worked on projects involving MMM or causal inference, include them in your application. Briefly describe the project, your role, and the impact it had on decision-making within the company.
Proofread Your Application: Before submitting, carefully proofread your application for any spelling or grammatical errors. A polished application reflects your attention to detail, which is crucial for a Data Scientist role.
How to prepare for a job interview at Career Wallet
✨Showcase Your Technical Skills
Be prepared to discuss your experience with the tech stack mentioned in the job description, particularly Databricks, SQL, and Python. Bring examples of past projects where you've successfully applied these tools, especially in Marketing Mix Modelling.
✨Communicate Clearly
Since excellent communication skills are a must, practice explaining complex data concepts in simple terms. Think about how you would present your findings to non-technical stakeholders and be ready to demonstrate this during the interview.
✨Demonstrate Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles, particularly related to causal inference techniques. Highlight how you approached these problems and the impact of your solutions on the business.
✨Understand the Company Culture
Research the company’s values and work environment. Since they thrive in a fast-paced, high-autonomy setting, be ready to share examples of how you've successfully worked independently and adapted to rapid changes in previous roles.
