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For Companies At a Glance
- Tasks: Lead data science initiatives, drive business growth, and engage with clients to deliver impactful solutions.
- Company: Join a growing consulting firm focused on Data and AI, shaping the future of data science.
- Benefits: Enjoy a competitive salary, hybrid work options, and opportunities for bonuses and professional growth.
- Why this job: Be at the forefront of innovation, making a real impact in business through data-driven insights.
- Qualifications: Strong background in data science, business development, and client engagement required.
- Other info: Ideal for strategic thinkers who thrive in collaborative environments.
The predicted salary is between 60000 - 84000 £ per year.
Job Description
Principal Data Scientist (Offering Lead)
Up to £100k base + benefits and bonus
London/ Hybrid
My growing consulting client is looking for a Principal Data Scientist (Offering Lead) within their Data and AI practice.
We are seeking a Principal Data Scientist with exceptional commercial acumen and a strong focus on driving business growth through data-driven insights and leveraging AI solutions.
This role is ideal for a strategic technical leader who combines deep technical expertise in data science, analytics, and machine learning with proven commercial experience and business development capabilities.
The ideal candidate will drive revenue growth across our target markets, identifying new opportunities, expanding client relationships, and delivering innovative Next Practice data science solutions that create measurable business impact.
This is a high-impact role that requires both technical expertise and commercial acumen to shape the future of data science within our organisation and build strong relationships with key stakeholders and clients.
Key Responsibilities
Commercial Strategy & Business Development: You will be the key role in executing our commercial strategy for AI and data science initiatives and consulting services. Develop go-to-market strategies for data science solutions, ensuring our service offerings expand to meet market demand and securing high-value client engagements. Lead business development activities, including client acquisition, relationship management, and strategic partnership development.
Client Engagement & Stakeholder Management: Act as a trusted advisor to leadership and senior stakeholders, translating complex data insights into actionable business strategies. Lead client presentations, proposal development, and commercial negotiations for data science projects. Manage key client relationships and ensure delivery of high-impact, commercially viable data science solutions.
Strategic Analytics & Decision Support: Lead the development of data science solutions that directly impact business outcomes, revenue generation, and strategic decision-making. Provide strategic advisory services on data monetisation, analytics strategy, and competitive intelligence. Oversee the design and implementation of commercial analytics platforms, customer segmentation models, and revenue optimisation algorithms.
Business Leadership & Team Development: Lead cross-functional teams combining data scientists, data engineers, and domain experts. Drive a culture of commercial awareness and business impact within the data science team. Collaborate closely with other pillars to identify and capitalise on commercial opportunities.
Performance & ROI Management: Establish metrics and frameworks to measure the commercial impact and ROI of data science initiatives. Develop business cases for data science investments and ensure projects deliver measurable commercial value. Drive continuous improvement in commercial processes through data-driven insights and analytics.
Key Competencies.
● Commercial Expertise: Strong track record in generating revenue, managing P&L responsibility, and driving commercial growth through data science initiatives. Experience in business development, client management, and strategic partnerships.
● Technical Proficiency: Deep understanding of data science methodologies, statistical analysis, machine learning algorithms, and analytics platforms (Python, SQL, vector stores and graphs, Power BI, Looker). Experience with commercial analytics tools and customer data platforms.
● Client Engagement: Proven experience engaging with senior executives, delivering data science strategies to business stakeholders, and managing commercial analytics projects. Strong presentation and communication skills for non-technical audiences.
● Strategic Leadership: Ability to translate business requirements into data science solutions and demonstrate clear commercial value. Experience leading commercially-focused data science teams and driving cross-functional collaboration.
Data Scientist employer: 83zero
Contact Detail:
83zero Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network with professionals in the data science and AI fields. Attend industry conferences, webinars, and local meetups to connect with potential colleagues and clients. Building relationships can lead to valuable insights and opportunities that may not be advertised.
✨Tip Number 2
Showcase your commercial acumen by engaging in discussions about business growth strategies related to data science. This could involve writing articles or participating in forums where you can share your insights on how data-driven solutions can impact revenue generation.
✨Tip Number 3
Prepare for interviews by familiarising yourself with the latest trends in data science and AI. Be ready to discuss how these trends can be leveraged for business development and client engagement, demonstrating your strategic thinking and technical expertise.
✨Tip Number 4
Research the company’s current projects and clients. Understanding their market position and challenges will allow you to tailor your conversations and demonstrate how your skills can directly contribute to their goals and objectives.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, analytics, and business development. Emphasise your commercial acumen and any successful projects that demonstrate your ability to drive revenue growth.
Craft a Compelling Cover Letter: In your cover letter, explain why you are the ideal candidate for the Principal Data Scientist role. Discuss your technical expertise, experience with AI solutions, and how you've successfully engaged with clients to deliver impactful data science solutions.
Showcase Technical Skills: Clearly outline your technical proficiency in data science methodologies, machine learning algorithms, and analytics platforms like Python and SQL. Provide examples of how you've applied these skills in previous roles to achieve business outcomes.
Highlight Leadership Experience: If you have experience leading teams or managing client relationships, make sure to include this in your application. Discuss how you've driven a culture of commercial awareness and collaboration within your teams.
How to prepare for a job interview at 83zero
✨Showcase Your Commercial Acumen
Make sure to highlight your experience in generating revenue and managing client relationships. Discuss specific examples where your data-driven insights led to measurable business growth, as this role heavily focuses on commercial strategy.
✨Demonstrate Technical Proficiency
Be prepared to discuss your technical skills in data science methodologies, machine learning algorithms, and analytics platforms. Familiarise yourself with tools like Python, SQL, and Power BI, and be ready to explain how you've used them in past projects.
✨Engage with Stakeholders
Practice how you would translate complex data insights into actionable strategies for non-technical audiences. Prepare to share experiences where you successfully engaged with senior executives and managed client expectations.
✨Prepare for Strategic Leadership Questions
Expect questions about your ability to lead cross-functional teams and drive a culture of commercial awareness. Think of examples that demonstrate your leadership style and how you've fostered collaboration among diverse teams.
