Job Description

At Mindera, we believe that software is built by people, for people, with high-performance systems that impact users worldwide. We are looking for a Lead Data Scientist to join an agile, collaborative team where your voice matters as much as your code.
n This role is therefore not about inventing a new strategy from scratch. It is about taking an agreed plan, implementing it well, and owning the recommendation models end to end in production.

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We value empathy, self-organization, and a positive attitude. If you are approachable, communicate clearly, and believe that team fit is just as important as technical expertise, you'll feel right at home here.

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At Mindera we encourage the use of AI to assist with coding and related tasks. We find a persons skill in engineering and software craft, has a big impact long term successful delivery, with or without AI. Our goal in the interview process is to understand the candidates knowledge and skill with engineering.

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If you need to, or plan to use AI, please be transparent with us when you're using it, to avoid issues and misunderstandings that can either: impact your chance of securing the role or impact your success at Mindera.

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National and international expected traveling time varies according to project/client and organizational needs: 0%-15% estimated.

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How You'll Contribute:
n You will work closely with the Data Science leadership, engineering teams, becoming the senior hands‐on Data Scientist responsible for progressing the recommendation capability in a disciplined and maintainable way.

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- Lead the consolidation of existing recommendation algorithms into a simpler, more coherent recommendation capability.
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- Implement the client's existing technical direction and agreed delivery plan.
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- Review current recommendation approaches and rationalise duplication, inconsistency and unnecessary complexity.
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- Develop, improve and productionise recommendation models across agreed customer and commercial use cases.
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- Own the full recommendation model lifecycle:
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- Data and feature development;
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- Model development;
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- Evaluation;
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- Production implementation;
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- Monitoring;
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- Retraining;
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- Ongoing optimisation.
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- Work directly in Databricks, using Python and PySpark to develop scalable production workloads.
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- Refactor exploratory or notebook-based Data Science code into maintainable production implementations.
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- Apply strong object-oriented design and software engineering principles to the recommendation codebase.
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- Create reusable and testable components for areas such as candidate generation, scoring, ranking, feature generation and evaluation.
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- Build appropriate automated testing around Data Science and ML code.
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- Work with engineering and platform teams on production integration without handing off ownership of the models themselves.
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- Define and maintain clear offline evaluation frameworks.
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- Support online experimentation and measurement of recommendation effectiveness.
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- Monitor production behaviour and take ownership of model quality once live.
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- Provide clear technical communication to both client stakeholders and the wider delivery team.
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This is a Data Science role with a much stronger production engineering expectation than a typical modelling-only position.

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We are looking for someone with strong experience in:

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- Recommendation systems, ranking or personalisation.
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- Python in production Data Science environments.
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- Databricks.
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- PySpark / Spark.
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- Large-scale customer, product or behavioural datasets.
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- Object-oriented programming.
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- Clean code and software design principles.
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- Modular, reusable and testable ML code.
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- Unit testing.
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- Git-based development.
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- CI/CD practices for Data Science or ML workloads.
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- Model evaluation and experimentation.
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- Deploying models into production.
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- Monitoring and maintaining production models.
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Relevant recommendation experience could include:

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- Collaborative filtering;
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- Content-based recommendation;
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- Hybrid approaches;
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- Candidate generation;
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- Ranking;
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- Learning to rank;
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- Embeddings;
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- Representation learning;
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- Personalisation;
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- Experimentation and incremental impact measurement.
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Experience with MLflow, Delta Lake, Databricks Workflows and model lifecycle management would be highly valuable.
n The strategic direction already exists.

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The successful person needs to be comfortable coming into an established environment, understanding the current state quickly, and executing and improving the agreed approach.

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You will likely be someone who has spent several years as a strong hands‐on Data Scientist and has gradually taken on more responsibility for how your models are engineered, deployed and operated.

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You should be equally comfortable:

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- Discussing recommendation methodology;
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- Reviewing model performance;
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- Writing Python;
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- Refactoring code;
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- Designing clean class structures;
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- Working in Databricks;
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- Debugging PySpark;
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- Writing tests;
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- Working through production issues;
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- Explaining technical trade-offs to stakeholders.
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You will need to be pragmatic.

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We don't need someone who immediately wants to redesign everything. They need someone who can understand the existing plan, challenge it where necessary, and then drive it through to a high-quality implementation.

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You will also be expected to:

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- Build credibility quickly with senior client Data Science stakeholders;
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- Operate independently within the client team;
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- Communicate progress, risks and technical decisions clearly;
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- Work collaboratively rather than positioning yourself as an external reviewer;
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- Balance client delivery priorities with good engineering practice;
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- Leave the recommendation capability in a stronger and more maintainable state than you found it.
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THE PERKS OF BECOMING A MINDER:

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- Private medical subscription
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- Private medical subscription for children
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- Counseling and psychotherapy services
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- Reimbursement for eyeglasses
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- Self-proposal salary process
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- Annual profit distribution, subject to company performance and board decision
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- Mindera Unit Plan
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- Adaptable benefits options (sports, medical, cultural, donations)
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- Trainings and learning opportunities to grow within your role
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- Coaching and development guidance
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- 25 days holiday
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- Flexibility to choose where you work from
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- Vacation incentive
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- Parties, gatherings & trips
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WHY MINDERA?

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We're thrilled to have the opportunity to share with you what it's like to be a part of the Mindera community.

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We're a group of friendly and talented individuals who work together to bring projects to life, in a fun, politics-free environment.

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Our culture is all about being adaptable and self-organized. We want Minders to take risks, make decisions, work together and feel free to be their most authentic selves, every single day.

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We work closely with our clients to truly understand their products and develop high-performance, resilient, and scalable software systems that make a real impact for their users and businesses, worldwide.

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We are proud of our work, we're always learning and growing in our Agile and collaborative environment, and we hope you'll love it here just as much as we do!

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Check out our Handbook & get to know us better: https://mindera.com/handbook.pdf

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Mindera around the world: Porto, Portugal | Aveiro, Portugal | Coimbra, Portugal | Leicester, UK | San Diego, USA | San Francisco, USA | Chennai, India | Bengaluru, India | Blumenau, Brazil | Cluj-Napoca, Romania | Valencia, Spain | Casablanca, Morocco | Melbourne, Victoria, Australia & Remote

📌 Lead Data Scientist (Victoria)
🏢 Mindera
📍 Victoria