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- Tasks: Transform complex data into engaging stories and actionable insights for stakeholders.
- Company: Join a dynamic consultancy focused on data and analytics, making waves in the industry.
- Benefits: Enjoy competitive pay, flexible freelance or permanent options, and a hybrid work environment.
- Why this job: Be part of innovative projects that drive real business impact through data storytelling and collaboration.
- Qualifications: 5+ years as a Senior Data Scientist with strong skills in SQL, Python, and data-driven storytelling.
- Other info: Work with top brands and cutting-edge technologies like AWS and machine learning.
The predicted salary is between 56000 - 84000 £ per year.
Role: Senior Data Scientist – Freelance and Permanent Option
Consulting Seniority: Senior Consultant – Director
Day rate: £500-£650/day
Salary (if permanent): £70k-£80k + up to 25%
Project duration: 2-3 months or Full time
Location: London/Hybrid
Project Blackbook – We build and manage consultancies’ on-demand freelance associate bench through a simple, cost-effective service.
We are partnered with a small but mighty strategy and data consultancy that is continuing to strengthen its data and analytics service lines. They are interested in candidates either on a freelance or permanent basis. What’s key are strong skills in data storytelling and stakeholder engagement.
Please apply directly via our website whenever possible and include your LinkedIn URL.
Tasks
- Data Storytelling: Develop and present data stories that translate complex analytical results into understandable and actionable insights for non-technical stakeholders
- Data Analysis and Insight Generation: Analyse large volumes of customer data from various sources (e.g., fuel purchases, convenience store transactions, car services, and EV charging) to uncover actionable business insights
- Data Wrangling: Clean, pre-process, and transform raw data into structured formats suitable for analysis using SQL and Python
- Model Development and Validation: Develop, tune, and validate machine learning models to predict customer behaviour. Surface insight that could be actioned to optimise marketing strategies and improve customer retention
- Visualisation Creation: Design and create compelling data visualisations to communicate findings to stakeholders
- Ad-hoc Business Queries: Respond to and solve ad-hoc business questions by extracting and analysing relevant data, providing timely and accurate insights
- Deterministic Record Linking: Employ deterministic record linking techniques, such as blocking, fingerprinting, aggregation, to normalisation, and similarity measures, to match and merge customer records accurately
- Collaborative Projects: Work collaboratively with cross-functional teams, including technology (e.g., data engineers, analysts, and architecture) and the business (e.g., marketing, operations) to action data-driven insights into business processes
- Cloud Integration: Use AWS services like Redshift and Athena to manage and analyse large datasets efficiently in the cloud environment
Requirements
- Senior Data Scientist with over 5 years of experience partnering with customer-focused businesses and renowned global brands, leveraging data-driven storytelling to engage key stakeholders and foster collaboration within dynamic teams
- Tech required: SQL, Python, Git, AWS (Amazon Redshift, Athena), Jupyter Notebook, Visual Studio Code (the client’s recommended IDE), deterministic record linking techniques, ML model development, good coding best practice
- Nice-to-have tech: Amazon SageMaker, PySpark, and MLOps
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Senior Data Scientist (Consulting Team) employer: Project Blackbook LTD
Contact Detail:
Project Blackbook LTD Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist (Consulting Team)
✨Tip Number 1
Make sure to showcase your experience in data storytelling during networking events or conversations. Highlight specific examples where you've successfully communicated complex data insights to non-technical stakeholders.
✨Tip Number 2
Engage with professionals in the data science community on platforms like LinkedIn. Share your insights on data analysis and visualization, and connect with individuals who work in consulting roles to learn more about their experiences.
✨Tip Number 3
Familiarize yourself with the latest trends in machine learning and cloud technologies, especially AWS services. Consider participating in relevant online courses or webinars to enhance your skills and demonstrate your commitment to continuous learning.
✨Tip Number 4
When reaching out to potential employers or connections, mention your proficiency in SQL and Python, as well as your experience with deterministic record linking techniques. This will help you stand out as a candidate who meets the technical requirements of the role.
We think you need these skills to ace Senior Data Scientist (Consulting Team)
Some tips for your application 🫡
Highlight Your Experience: Make sure to emphasize your experience as a Senior Data Scientist, particularly your work with data storytelling and stakeholder engagement. Use specific examples that showcase your ability to translate complex data into actionable insights.
Showcase Technical Skills: Clearly list your technical skills relevant to the role, such as SQL, Python, and AWS services. Mention any experience with machine learning model development and data wrangling techniques, as these are crucial for the position.
Include Your LinkedIn URL: Since the job description specifically requests it, don’t forget to include your LinkedIn URL in your application. This allows the hiring team to easily access your professional background and network.
Tailor Your Application: Customize your CV and cover letter to align with the job description. Highlight relevant projects and experiences that demonstrate your ability to work collaboratively with cross-functional teams and deliver data-driven insights.
How to prepare for a job interview at Project Blackbook LTD
✨Showcase Your Data Storytelling Skills
Prepare to discuss how you've transformed complex data into compelling narratives. Use specific examples from your past experiences where your storytelling led to actionable insights for non-technical stakeholders.
✨Demonstrate Technical Proficiency
Be ready to talk about your experience with SQL, Python, and AWS services like Redshift and Athena. Highlight any projects where you utilized these technologies to manage and analyze large datasets.
✨Highlight Collaborative Experiences
Since the role involves working with cross-functional teams, share examples of how you've successfully collaborated with different departments, such as marketing or operations, to implement data-driven solutions.
✨Prepare for Model Development Discussions
Expect questions about your experience in developing and validating machine learning models. Be prepared to explain your approach to model tuning and how your insights have optimized marketing strategies or improved customer retention.
