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Netrolynx AI

Data Science Manager

United Kingdom
Posted about 13 hours ago
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About The Company

Data Idols is a leading data-driven consultancy specializing in delivering innovative analytics and AI solutions to a diverse range of clients across various industries. With a strong focus on leveraging data to drive strategic decision-making, Data Idols prides itself on its expert team of data scientists, engineers, and consultants who work collaboratively to solve complex business challenges. The company is committed to fostering a culture of continuous learning, innovation, and excellence, ensuring that clients stay ahead in a rapidly evolving digital landscape. Through its tailored approach and cutting-edge technologies, Data Idols aims to empower organizations to unlock the full potential of their data assets and achieve sustainable growth.

About The Role

Data Idols is seeking a highly skilled and strategic Data Science Manager to join its dynamic team. This leadership role is based in London with a hybrid working model, offering a unique opportunity to influence high-impact projects within a prominent UK retail brand. The successful candidate will oversee a talented team of Data Scientists, driving the development and deployment of advanced analytics and machine learning models that enhance customer engagement, personalization, and business performance. As a key player at the intersection of data science, customer insights, and strategic planning, you will be instrumental in shaping the company's approach to customer-centric data initiatives. Your expertise will help translate complex behavioral data into actionable insights, enabling the client to deliver personalized experiences at scale and stay competitive in a fast-changing retail environment.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Strong

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Qualifications

  • Proven experience managing or leading Data Science teams within a commercial or corporate environment.
  • Strong expertise in machine learning, statistical modeling, customer analytics, and personalization techniques.
  • Hands-on experience developing and deploying customer-focused models in production settings.
  • Excellent stakeholder management skills, with the ability to communicate complex technical concepts to non-technical audiences.
  • Demonstrated ability to translate data insights into strategic business recommendations.
  • Relevant educational background, typically a Master’s or PhD in Data Science, Statistics, Computer Science, or a related field.
  • Experience with MLOps, experimentation frameworks, and data engineering best practices is highly desirable.

Responsibilities

The successful candidate will be responsible for leading the technical and strategic direction of the data science team, including:

  • Overseeing the design, development, and deployment of machine learning models that deliver measurable customer and commercial impact.
  • Establishing best practices for data science workflows, including experimentation, model validation, and MLOps processes.
  • Collaborating with cross-functional teams such as product management, marketing, and engineering to align data initiatives with business goals.
  • Translating complex customer and behavioral data into clear, actionable insights and recommendations for stakeholders.
  • Supporting the growth and development of team members through mentorship, training, and performance management.
  • Ensuring the scalability, reliability, and robustness of data science solutions in production environments.
  • Driving innovation by staying abreast of emerging trends and technologies in data science and AI.

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Benefits

At Data Idols, we value our employees and offer a comprehensive benefits package designed to support your professional and personal growth. These include competitive salary packages, performance-based bonuses, flexible working arrangements, and opportunities for continuous learning and development. Our benefits also extend to health and wellness programs, generous holiday allowances, and a collaborative work environment that encourages innovation and knowledge sharing. We believe in fostering a culture that promotes work-life balance, diversity, and inclusion, ensuring all team members feel valued and empowered to contribute their best.

Equal Opportunity

Data Idols is an equal opportunity employer. We are committed to creating an inclusive environment where diversity is celebrated and all employees are treated with fairness and respect. We do not discriminate based on race, gender, age, religion, sexual orientation, disability, or any other protected characteristic. We believe that a diverse workforce enhances our ability to innovate and serve our clients effectively, and we actively promote a culture of equity and inclusion at all levels of the organization.

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Skills

Data Science
Machine Learning
Statistical Modeling
Customer Analytics
Personalization Techniques
Stakeholder Management
Data Insights
MLOps
Data Engineering

Location

United Kingdom

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