Lead Data Scientist

Mindera

City of Melbourne

On-site

AUD 180,000 - 240,000

Full time

4 days ago

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Benefits offered by this job

Private medical

Private medical (children)

Counseling services

Eyewear reimbursement

Profit distribution

Mindera Unit Plan

Flexible benefits

Learning opportunities

Coaching

25 days holiday

Work flexibility

Vacation incentive

Social events

Job summary

Mindera is seeking a Lead Data Scientist to join an agile, collaborative team where your voice matters as much as your code. You will own the recommendation models end to end in production, implementing an agreed plan and producing robust, testable code.

You’ll work with Data Science leadership and engineering teams in Databricks with Python and PySpark to productionise features, refactor notebooks, and apply solid OO design. Strong communication with clients and delivery teams is essential.

Qualifications

Strong production-grade data science experience.
Expertise building and deploying end-to-end recommendation models.
Proficiency with Python, Databricks and Spark in production.

Responsibilities

Lead consolidation and simplification of recommendation algorithms.
Develop, productionise and monitor ML models across use cases.
Own full model lifecycle: data, feature, model, evaluation, deployment, monitoring.

Skills

Python in production DS

Databricks

PySpark / Spark

Object-oriented programming

Clean code

Modular ML code

Unit testing

Git

CI/CD for ML

Model evaluation

Experimentation

Deployment to production

Monitoring production models

Tools

Databricks

PySpark

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.
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.

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.

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.

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.

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

How You’ll Contribute:
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.

Lead the consolidation of existing recommendation algorithms into a simpler, more coherent recommendation capability.
Implement the client’s existing technical direction and agreed delivery plan.
Review current recommendation approaches and rationalise duplication, inconsistency and unnecessary complexity.
Develop, improve and productionise recommendation models across agreed customer and commercial use cases.
Own the full recommendation model lifecycle:

Data and feature development;
Model development;
Evaluation;
Production implementation;
Monitoring;
Retraining;
Ongoing optimisation.

Work directly in Databricks, using Python and PySpark to develop scalable production workloads.
Refactor exploratory or notebook-based Data Science code into maintainable production implementations.
Apply strong object-oriented design and software engineering principles to the recommendation codebase.
Create reusable and testable components for areas such as candidate generation, scoring, ranking, feature generation and evaluation.
Build appropriate automated testing around Data Science and ML code.
Work with engineering and platform teams on production integration without handing off ownership of the models themselves.
Define and maintain clear offline evaluation frameworks.
Support online experimentation and measurement of recommendation effectiveness.
Monitor production behaviour and take ownership of model quality once live.
Provide clear technical communication to both client stakeholders and the wider delivery team.

This is a Data Science role with a much stronger production engineering expectation than a typical modelling-only position.

We are looking for someone with strong experience in:

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

Relevant recommendation experience could include:

Collaborative filtering;
Content-based recommendation;
Hybrid approaches;
Candidate generation;
Ranking;
Learning to rank;
Embeddings;
Representation learning;
Personalisation;
Experimentation and incremental impact measurement.

Experience with MLflow, Delta Lake, Databricks Workflows and model lifecycle management would be highly valuable.
The strategic direction already exists.

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

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.

You should be equally comfortable:

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

You will need to be pragmatic.

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.

You will also be expected to:

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

THE PERKS OF BECOMING A MINDER:

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

WHY MINDERA?

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

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

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.

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.

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!

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

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