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Senior Data Scientist

INSTANDA is the worlds first no code platform for Insurance. A pioneering Insurtech, we’re revolutionising the insurance industry by offering insurers a versatile tool to create, manage, and distribute digital insurance products. Our innovative technology empowers insurance carriers to adapt swiftly to market demands and navigate the evolving landscape. Our Technology is consistently recognised as the best policy administration platform for innovative insurers, winning awards in both the UK and US.

INSTANDA has grown significantly in recent years and we are now a team of 200+ employees globally, with partnerships that operate worldwide. We’re continuing to grow our business and our People Operations team is at the forefront of our growth plans.

Follow us to learn more: Instanda.com | LinkedIn | Twitter | YouTube

The Role:

We’re looking for a Senior Data Scientist to lead and scale our AI solution efforts. This role is perfect for an experienced professional who has consistently delivered high-impact AI and ML solutions, led cross-functional initiatives, and influenced strategic decisions through data. You’ll have substantial autonomy, ownership, and a voice in shaping the product roadmap, with significant opportunities for growth and leadership.

This role isUK based, primarily remote working with some travel required to our London Office.

What you will do:

  • Independently design, develop, and deploy robust, scalable AI/ML solutions tailored to business needs.
  • Lead the full model lifecycle: problem formulation, data exploration, model development, validation, deployment, and monitoring.
  • Collaborate with engineering and product teams to embed models into production systems and deliver end-to-end solutions.
  • Act as a technical leader and mentor within the data science team, supporting the growth of junior colleagues.
  • Identify model/data drift and implement retraining pipelines or adaptation strategies to ensure sustained model performance.
  • Champion the use of interpretable AI and communicate insights clearly to both technical and non-technical stakeholders.
  • Engage with senior stakeholders to understand business objectives and translate them into data-driven strategies.
  • Contribute to and evolve our AI/ML best practices, architecture, and toolchain.
  • Stay ahead of AI/ML trends and evaluate new tools or methodologies for potential use.

Essential:

  • 5+ years of proven experience delivering AI/ML models in production environments.
  • Advanced knowledge of machine learning, deep learning (e.g., XGBoost, LSTMs, transformers), and statistical modeling.
  • Proficient in Python and machine learning libraries such as Scikit-learn, TensorFlow, PyTorch, etc.
  • Hands-on experience with MLOps tools and practices: model tracking, drift detection, continuous learning.
  • Strong background in data processing, feature engineering, and scalable ML pipelines.
  • Experience working in cloud environments (Azure preferred) and with containerization tools (Docker, Kubernetes).
  • Demonstrated success engaging with senior stakeholders and influencing decision-making with data.
  • Excellent communication and storytelling skills with the ability to convey complex concepts clearly.
  • Strong leadership qualities: ownership, initiative, mentoring, and strategic thinking.
  • Self-starter mindset with a track record of thriving in fast-moving, startup-like environments.

Desirable:

  • Experience in the insurance or financial services domain.
  • Familiarity with explainable AI (e.g., SHAP, LIME) and responsible AI practices.
  • Knowledge of software engineering principles (CI/CD, version control, testing).

 

  • A high-autonomy role with substantial influence over AI strategy and execution.
  • Opportunities for career growth into technical leadership or product strategy.
  • A collaborative, startup-style culture that encourages innovation and rapid iteration.
  • Access to cutting-edge tools and technologies across the AI/ML landscape.
  • Competitive salary
  • Generous 28 days holiday allowance, in addition to public holidays.
  • For every year of service you complete, we’ll give you an additional days holiday (max. 5 days)
  • One Dynamic Day per month on top of your holiday allowance to spend time doing the things you want to do or simply catching up with life admin.
  • Freedom Pass work up to 4 weeks of the year from anywhere.
  • FlexiBank you decide when to use your public holiday allocation.
  • Hybrid Working approach varying with the nature of your role.
  • Life cover; income protection and participation in the company pension scheme
  • All employees are included in the company discretionary bonus scheme
  • £100 per month to put towards wellness activities.
  • Annual learning & development allowance of £1,250
  • Free access to LinkedIn learning and Microsoft ESI learning platform

If you're ready to make a meaningful impact and lead transformative AI initiatives in a dynamic tech environment, we'd love to hear from you. Apply now and shape the future of AI at INSTANDA.

Our company was built by looking at the world through a different lens and our culture today reflects that by encouraging you to be yourself, speak your mind, and share your opinions. We want people who want to push themselves, be part of something great, and be prepared to challenge if they think there is a better way. Collaboration sits at the heart of how we operate, it has fueled our growth enormously and our aim to be ‘world class’.                                                                                                     

We want everyone to be the best they can be throughout our recruitment process; if you require any additional adjustments please let us know. Visit instanda.com/careers for more information

INSTANDA has an in-house recruitment team, which focuses on sourcing great candidates directly.  INSTANDA does not accept unsolicited resumes from agency or search firm recruiters.  Fees will not be paid in the event a candidate submitted by a recruiter without an agreement in place is hired.  When we do use agencies, we have a PSL in place, so please do not contact managers directly.

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Average salary estimate

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What You Should Know About Senior Data Scientist, Instanda

INSTANDA, a pioneering Insurtech company, is on the lookout for a Senior Data Scientist to elevate our AI solutions initiatives. We're not just transforming how insurance works; we're changing the entire industry with our innovative no-code platform that enables insurers to create and manage digital products effortlessly. As a Senior Data Scientist at INSTANDA, you'll have the unique opportunity to independently design, develop, and deploy AI/ML solutions tailored for our growing business needs. You’ll take the lead on the entire model lifecycle—from problem formulation to deploying robust, scalable solutions that truly make an impact. Collaboration is key here, as you will work directly with our engineering and product teams to embed your models into our systems. This role isn’t just about crunching numbers; you’ll also mentor junior colleagues, advocate for interpretable AI, and engage with senior stakeholders to translate their business objectives into actionable data strategies. With your extensive experience in model development and a strong command over Python and various ML libraries, you will influence strategic decisions and contribute to evolving our AI best practices. You'll thrive in a flexible, hybrid work environment with access to state-of-the-art tools and a supportive culture that celebrates innovation and collaboration. If you're ready for a role that offers substantial autonomy and career growth, come join our dynamic team at INSTANDA!

Frequently Asked Questions (FAQs) for Senior Data Scientist Role at Instanda
What are the key responsibilities of a Senior Data Scientist at INSTANDA?

As a Senior Data Scientist at INSTANDA, your primary responsibilities will include designing and deploying AI/ML solutions tailored to business needs, leading the entire model lifecycle, and collaborating with product and engineering teams to ensure seamless integration of solutions into production systems. You will also take on a mentoring role for junior data scientists and communicate AI insights to stakeholders effectively.

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What qualifications do I need to apply for the Senior Data Scientist position at INSTANDA?

To qualify for the Senior Data Scientist role at INSTANDA, candidates should possess a minimum of 5 years of experience delivering AI/ML models in production settings. Advanced knowledge in machine learning, experience with Python and machine learning libraries like Scikit-learn or TensorFlow, and familiarity with cloud environments (preferably Azure) are essential. Strong leadership and communication skills are also vital, as you'll be engaging with stakeholders and mentoring junior team members.

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What skills are valued in a Senior Data Scientist at INSTANDA?

Skills that are highly valued for the Senior Data Scientist role at INSTANDA include proficiency in machine learning and deep learning, hands-on experience with MLOps tools, expertise in data processing and feature engineering, and excellent storytelling skills to articulate complex concepts. A self-starter attitude and the ability to thrive in a fast-moving tech environment are also crucial.

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What can I expect in terms of career growth as a Senior Data Scientist at INSTANDA?

At INSTANDA, career growth as a Senior Data Scientist is supported through opportunities to influence AI strategy and execution. The role allows for substantial leadership influence, and there are potential paths leading into technical leadership or product strategy. Additionally, the company advocates for ongoing learning and offers a generous annual development allowance.

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Is the Senior Data Scientist position at INSTANDA a remote role?

Yes! The Senior Data Scientist role at INSTANDA is primarily remote, encouraging a flexible work environment. However, it does require some travel to our London office for team collaboration and strategy meetings, making it accessible while still offering the comfort of remote work.

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Common Interview Questions for Senior Data Scientist
Can you describe your experience with building and deploying AI/ML models?

When responding to this question, provide specific examples of AI/ML models you've built and deployed, focusing on the tools and techniques you used. Emphasize the outcomes of these projects and how they contributed to business objectives, demonstrating the impact of your work.

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How do you ensure the performance of an AI/ML model over time?

A good answer to this question would include discussing techniques such as monitoring model drift, setting up retraining pipelines, and actively evaluating model metrics. Highlight your experience with continuous learning practices and explain how you adapt models to maintain accuracy and relevance.

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What steps do you take while collaborating with cross-functional teams?

You should articulate a collaborative approach that includes regular communication, setting clear expectations, and actively engaging with team members to gather insights. Mention any tools or methods you use to facilitate collaboration and how you ensure everyone's objectives are aligned.

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How do you handle challenges when integrating ML models into production systems?

Discuss specific challenges you faced, such as version control or operationalization hurdles, and explain how you navigated those issues. Emphasize the importance of collaboration with engineering teams and how you leverage MLOps practices to streamline deployment processes.

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Describe a time when you had to communicate complex data insights to non-technical stakeholders.

Offer a concise example where you successfully translated technical data insights into understandable terms for a non-technical audience. Highlight your communication methods, such as using visualizations or simple storytelling, that helped stakeholders grasp the necessary concepts.

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What tools do you use for model tracking and performance monitoring?

Mention any MLOps tools you've used for model tracking, such as MLflow, TensorBoard, or DVC. Providing context around their capabilities and how you have utilized them in past projects will showcase your technical knowledge and operational experience in managing ML models.

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How do you stay current with the latest trends in AI and ML?

You can talk about your commitment to continuous education, including following industry leaders, attending conferences, or participating in professional groups. Mention any resources like journals or online courses that keep you informed and how you incorporate new knowledge into your projects.

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What approaches do you take to ensure your AI solutions are interpretable?

Discuss techniques for creating interpretable models, like using SHAP or LIME for interpretability, and emphasize the importance of communicating insights effectively to stakeholders. Show your understanding of why interpretability matters, especially in regulated industries like insurance.

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How do you prioritize tasks when working on multiple AI projects?

Articulate a structured approach to prioritization, perhaps outlining how you assess project impact and urgency. Discuss tools or methodologies you use, like Agile, to manage your time effectively and ensure all projects progress smoothly.

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Can you describe your experience mentoring junior data scientists?

Share specific instances where you provided guidance to junior colleagues, highlighting your mentoring style and the impact it had on their growth. Discuss how fostering an environment of learning and collaboration has positively influenced your team.

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Full-time, hybrid
DATE POSTED
April 15, 2025

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