Lead Data Scientist

Lead Data Scientist

Full-Time 80000 - 100000 € / year (est.) Home office (partial)
DLA Piper

At a Glance

  • Tasks: Lead innovative data and AI projects across legal and business services.
  • Company: Global law firm committed to innovation and inclusion.
  • Benefits: Competitive salary, diverse culture, and opportunities for professional growth.
  • Other info: Join a diverse team and help shape the future of legal services.
  • Why this job: Make a real impact with cutting-edge AI solutions in a dynamic environment.
  • Qualifications: Experience in Data, ML, and GenAI; strong Python and SQL skills.

The predicted salary is between 80000 - 100000 € per year.

We are seeking a Lead Data Scientist to define and deliver data and AI-enabled products and capabilities across legal, knowledge, finance, and business services. This is a senior, hands-on leadership role for someone who can set direction, translate high-value problems into scalable solutions, design robust data and GenAI architectures, and drive delivery into production with clear governance and measurable outcomes. You will operate at the intersection of solution architecture, applied ML/GenAI, product delivery, and senior stakeholder management. You will lead use cases such as document intelligence, knowledge retrieval and search, due diligence, pricing/profitability insights, workflow automation, and agent-enabled assistants, while establishing the evaluation, monitoring, Responsible AI controls, and adoption metrics needed to scale impact across the firm.

Responsibilities

  • Set the technical strategy and solution direction for the firm’s Data & AI portfolio across legal and business functions.
  • Co-create the AI roadmap with senior stakeholders, prioritising opportunities by business value, feasibility, risk, and platform readiness.
  • Turn ambiguous problem statements into target architectures, delivery plans, and clear technical requirements.
  • Lead the design and implementation of ML, NLP, GenAI, and Retrieval-Augmented Generation (RAG) solutions.
  • Own the solution architecture patterns for orchestration, retrieval, evaluation, monitoring, security, and human-in-the-loop review.
  • Deliver document-heavy AI use cases (e.g., OCR/document intelligence, clause extraction, due diligence, knowledge search, workflow automation).
  • Partner with product and platform engineering, knowledge, legal tech, and business teams to integrate AI into core systems and workflows.
  • Assess third-party vendors/tools and advise on capability fit, integration effort, governance, commercial model, and strategic longevity.
  • Define standards for experimentation, validation, model quality, and release readiness (evaluation, testing, and monitoring).
  • Coach and mentor data scientists, analysts, and cross-functional contributors; uplift delivery maturity and engineering standards.

About You

  • Significant experience leading Data, ML, and GenAI initiatives in complex enterprise and/or regulated environments.
  • Proven ability to blend strategy, stakeholder leadership, and hands-on technical delivery to achieve measurable outcomes.
  • Strong working knowledge of Python and SQL, ML workflows, and modern GenAI tooling.
  • Experience building statistical and measurement frameworks (e.g., adoption/usage, quality, value tracking, experimentation design).
  • Strong experience with LLM applications, RAG, embeddings, vector search, and custom retrieval patterns.
  • Experience designing and delivering solutions on Azure and Databricks (including Azure OpenAI and Azure AI Foundry or equivalent capabilities).
  • Experience with document-heavy AI use cases (OCR/document intelligence, search, summarisation, extraction, and classification).
  • Strong stakeholder management skills, with the ability to influence senior leaders and align IT and business teams.
  • Track record of defining governance, evaluation, security, and Responsible AI controls for deployed solutions.
  • Ability to lead multi-disciplinary delivery teams and mentor technical practitioners while remaining credible at architecture depth.

About Us

We're a global law firm helping our clients achieve their goals wherever they do business. Our pursuit of innovation has transformed our delivery of legal services. With offices in the Americas, Europe, the Middle East, Africa and Asia Pacific, we deliver exceptional outcomes on cross-border projects, critical transactions and high-stakes disputes. At DLA Piper, we understand that inclusion is not a one-size-fits-all concept. We embrace and celebrate the range of perspectives, backgrounds and experiences that each individual brings to our firm. By fostering a culture that welcomes and appreciates all aspects of our individuality, we ensure that everyone has the opportunity to succeed. Our commitment to inclusion and positive social impact enables us to provide exceptional service to our clients and communities, while nurturing a unique and inclusive culture for all our people. We welcome the unique contribution that you will bring to our firm and actively encourage applications from all talented people – however your talent is packaged, whatever your background or circumstance and regardless of how you identify.

Lead Data Scientist employer: DLA Piper

DLA Piper is an exceptional employer that champions innovation and inclusivity, making it a prime choice for professionals seeking to make a meaningful impact in the legal sector. With a strong focus on employee growth, we offer robust mentorship opportunities and a collaborative work culture that values diverse perspectives. Our global presence ensures that you will be part of transformative projects while enjoying the benefits of a supportive environment that prioritises your professional development and well-being.

DLA Piper

Contact Detail:

DLA Piper Recruiting Team

StudySmarter Expert Advice🤫

We think this is how you could land Lead Data Scientist

Tip Number 1

Network like a pro! Reach out to folks in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.

Tip Number 2

Show off your skills! Create a portfolio showcasing your projects, especially those related to data science and AI. This gives potential employers a taste of what you can do.

Tip Number 3

Prepare for interviews by practising common questions and scenarios specific to data science roles. We recommend doing mock interviews with friends or using online platforms to get comfortable.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love hearing from passionate candidates like you!

We think you need these skills to ace Lead Data Scientist

Data Science
Machine Learning (ML)
Generative AI (GenAI)
Natural Language Processing (NLP)
Solution Architecture
Python
SQL

Some tips for your application 🫡

Tailor Your CV:Make sure your CV speaks directly to the Lead Data Scientist role. Highlight your experience with ML, GenAI, and any relevant projects that showcase your ability to deliver data-driven solutions in complex environments.

Craft a Compelling Cover Letter:Use your cover letter to tell us why you're the perfect fit for this role. Share specific examples of how you've led data initiatives and collaborated with stakeholders to achieve measurable outcomes.

Showcase Your Technical Skills:Don’t forget to mention your proficiency in Python, SQL, and any experience with Azure or Databricks. We want to see how your technical skills align with our needs for robust data architectures and AI solutions.

Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and ensure it gets the attention it deserves!

How to prepare for a job interview at DLA Piper

Know Your Tech Inside Out

As a Lead Data Scientist, you'll need to showcase your expertise in Python, SQL, and modern GenAI tooling. Brush up on your technical skills and be ready to discuss specific projects where you've implemented these technologies. Prepare to explain your thought process behind designing ML workflows and how you’ve tackled complex data challenges.

Master the Art of Stakeholder Management

This role requires strong stakeholder management skills, so think about examples where you've influenced senior leaders or aligned IT and business teams. Be prepared to discuss how you prioritised opportunities by business value and feasibility in past projects. Show that you can communicate complex ideas clearly and effectively.

Demonstrate Your Leadership Skills

You'll be leading multi-disciplinary teams, so highlight your experience in coaching and mentoring others. Share specific instances where you've uplifted delivery maturity and engineering standards. Discuss how you’ve managed cross-functional contributors and ensured everyone is aligned towards common goals.

Prepare for Scenario-Based Questions

Expect scenario-based questions that assess your problem-solving abilities. Think about how you would turn ambiguous problem statements into clear technical requirements and delivery plans. Be ready to outline your approach to designing and implementing AI solutions, especially in document-heavy use cases like OCR and knowledge retrieval.