At a Glance
- Tasks: Lead advanced analytics and AI/ML projects to create impactful data-driven products.
- Company: Join a dynamic team focused on innovation and real-world solutions in data science.
- Benefits: Enjoy a flexible contract role with opportunities for growth and skill development.
- Why this job: Make a real impact in a fast-paced environment while collaborating with diverse teams.
- Qualifications: Bachelor's, Master's, or PhD in Data Science or related field; proficiency in Python or R required.
- Other info: This is a 6-month contract role ideal for self-driven data scientists eager to deliver results.
The predicted salary is between 54000 - 84000 ÂŁ per year.
Overview
We’re seeking a Senior Data Scientist to lead the development of advanced analytics and AI/ML solutions that unlock real value across our business. This is a contract role for 6 months.
In this contract role, you\’ll work with proprietary and B2B research datasets to design, deliver, and scale data-driven products. Collaborating closely with teams in Product, Research, and Technology, you\’ll help turn strategic ideas into working MVPs—ensuring high standards of methodology, quality, and business relevance throughout.
You’ll also help shape the data science environment by working alongside our tech teams to support a robust and flexible infrastructure, including sandbox environments for onboarding and evaluating new data sources.
This is a great opportunity for a self-driven, impact-oriented data scientist who thrives in a fast-paced, cross-functional setting—and is eager to deliver meaningful results in a short time frame.
Main Duties and Responsibilities
- Spearhead and execute complex data science projects using a combination of open-source and cloud tools, driving innovation and delivering actionable insights.
- Develop and deploy advanced machine learning models using cloud-based platforms.
- Collaborate with product managers and designers to ensure the feasibility of product extensions and new products based on existing proprietary, quantitative, and qualitative datasets.
- Work with outputs from Research and historical data to identify consistent and inconsistent product features and document precise requirements for improved consistency.
- Collaborate with designers, Tech colleagues, and expert users to come up with engaging ways to visualize data and outliers/exceptions for non-technical audiences.
- Design and develop novel ways to showcase and highlight key analysis from complex datasets, including joining across datasets that do not perfectly match.
- Collaborate with Product, Tech, Research, and other stakeholders to understand and define a new, marketable product from existing data.
- Create and present progress reports and ad-hoc reviews to key stakeholders and teams.
- Constantly think about and explain to stakeholders how analytics “products” could be refined and productionized in the future.
- Work with Tech colleagues to improve the Data Science workspace, including providing requirements for Data Lake, Data Pipeline, and Data Engineering teams.
- Expand on the tools and techniques already developed.
- Help us understand our customers (both internal and external) better so we can provide the right solutions to the right people, including proactively suggesting solutions for nebulous problems.
- Be responsible for the end-to-end Data Science lifecycle: investigation of data, from data cleaning to extracting insights and recommending production approaches.
- Responsible for demonstrating value addition to stakeholders.
- Coach, guide, and nurture talent within the data science team, fostering growth and skill development.
Skills and Experience
- Delivering significant and valuable analytics projects/assets in industry and/or professional services.
- Proficiency in programming languages such as Python or R, with extensive experience with LLMs, ML algorithms, and models.
- Experience with cloud services like Azure ML Studio, Azure Functions, Azure Pipelines, MLflow, Azure Databricks, etc., is a plus.
- Experience working in Azure/Microsoft environments is considered a real plus.
- Proven understanding of data science methods for analyzing and making sense of research data outputs and survey datasets.
- Fluency in advanced statistics, ideally through both education and experience.
Person Specification
- Bachelor\’s, Master\’s, or PhD in Data Science, Computer Science, Statistics, or a related field.
- Comfortable working with uncertainty and ambiguity, from initial concepts through iterations and experiments to find the right products/services to launch.
- Excellent problem-solving and strong analytical skills.
- Proven aptitude to learn new tools, technologies, and methodologies.
- Understanding of requirements for software engineering and data governance in data science.
- Proven ability to manage and mentor data science teams.
- Evidence of taking a company or department on a journey from Analytics to Data Science to AI and ML deployed at scale.
- Ability to translate complex analysis findings into clear narratives and actionable insights.
- Excellent communication skills, with the ability to listen and collaborate with non-technical and non-quantitative stakeholders.
- Experience working with client-facing and Tech teams to ensure proper data collection, quality, and reporting formats.
- Experience presenting investigations and insights to audiences with varying skill sets and backgrounds.
- Nice to have: experience working with market research methods and datasets.
- Nice to have: experience in the professional services or legal sector.
- B2B market research experience would be a significant plus.
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Senior Data Scientist employer: Chambers & Partners
Contact Detail:
Chambers & Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as Azure ML Studio and Databricks. Having hands-on experience or projects showcasing your proficiency with these platforms can set you apart from other candidates.
✨Tip Number 2
Network with professionals in the data science field, especially those who have experience in B2B market research. Engaging with them on platforms like LinkedIn can provide insights into the role and may even lead to referrals.
✨Tip Number 3
Prepare to discuss your previous projects in detail, particularly those that involved collaboration across teams. Highlighting your ability to work with product managers and tech teams will demonstrate your fit for this cross-functional role.
✨Tip Number 4
Showcase your problem-solving skills by preparing examples of how you've tackled complex data challenges in the past. Be ready to explain your thought process and the impact of your solutions on the business.
We think you need these skills to ace Senior Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly with advanced analytics and AI/ML solutions. Emphasise your proficiency in programming languages like Python or R, and any experience with cloud services such as Azure.
Craft a Compelling Cover Letter: In your cover letter, explain why you are the perfect fit for the Senior Data Scientist role. Discuss your experience with complex data science projects and how you've successfully collaborated with cross-functional teams to deliver impactful results.
Showcase Your Projects: Include specific examples of past projects where you developed and deployed machine learning models. Highlight any innovative solutions you created and the tangible outcomes they produced, especially in fast-paced environments.
Prepare for Technical Questions: Be ready to discuss your technical skills in detail during the application process. Prepare to explain your understanding of data science methods, your experience with LLMs and ML algorithms, and how you approach problem-solving in uncertain situations.
How to prepare for a job interview at Chambers & Partners
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in programming languages like Python or R, and your experience with machine learning algorithms. Highlight specific projects where you've successfully implemented these skills, especially using cloud services like Azure.
✨Demonstrate Problem-Solving Abilities
Expect to face scenario-based questions that assess your problem-solving skills. Prepare examples of how you've tackled complex data challenges in the past, focusing on your analytical approach and the impact of your solutions.
✨Communicate Clearly with Non-Technical Stakeholders
Since you'll be collaborating with various teams, practice explaining complex data concepts in simple terms. Use examples from your previous work to illustrate how you’ve effectively communicated insights to non-technical audiences.
✨Prepare for Collaborative Discussions
As this role involves working closely with product managers and designers, think about how you can contribute to team discussions. Be ready to share ideas on how to turn strategic concepts into actionable products, showcasing your collaborative mindset.