Lead Data Scientist

Mindera

. Lead consolidation of existing recommendation algorithms into a simpler, coherent recommendation capability .

Posted 9/15/2026full-timeCluj-Napoca • RomaniaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates strong expertise in developing and optimizing recommendation systems, with a focus on Python and PySpark for production environments. Capable of implementing clean code practices, model evaluation, and maintaining production models while effectively communicating technical information to stakeholders.

Highest-signal resume keywords

Recommendation SystemsPython ProgrammingDatabricksPySparkModel Evaluation

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Hard Skills

Recommendation SystemsPython ProgrammingPySparkObject-Oriented ProgrammingUnit TestingCI/CD PracticesModel DeploymentModel MonitoringCollaborative FilteringContent-Based Recommendation

Soft Skills

Clear CommunicationIndependent OperationCollaborative ApproachCredibility Building

Tools & Technologies

DatabricksMLflowDelta LakeGit

Industry Keywords

Data ScienceMachine LearningPersonalizationRankingFeature Generation

Tech Stack

Tools & technologies

PySparkPythonSpark

About the role

Key responsibilities & impact

Lead consolidation of existing recommendation algorithms into a simpler, coherent recommendation capability
Implement the client’s existing technical direction and agreed delivery plan
Review recommendation approaches and rationalise duplication, inconsistency and unnecessary complexity
Develop, improve and productionise recommendation models for customer and commercial use cases
Own data and feature development, model development, evaluation, production implementation, monitoring, retraining and ongoing optimisation
Develop scalable production workloads in Databricks using Python and PySpark
Refactor exploratory or notebook-based Data Science code into maintainable production implementations
Apply object-oriented design and software engineering principles to the recommendation codebase
Create reusable and testable components for candidate generation, scoring, ranking, feature generation and evaluation
Build automated testing around Data Science and ML code
Work with engineering and platform teams on production integration while retaining model ownership
Define and maintain offline evaluation frameworks
Support online experimentation and measurement of recommendation effectiveness
Monitor production behaviour and own model quality after launch
Communicate technical information clearly to client stakeholders and the wider delivery team
Build credibility with senior client Data Science stakeholders
Operate independently within the client team
Communicate progress, risks and technical decisions clearly
Leave the recommendation capability more maintainable than it was found
Travel according to project, client and organisational needs, estimated at 0%-15%

Requirements

What you’ll need

Strong experience in recommendation systems, ranking or personalisation
Strong Python experience in production Data Science environments
Experience with Databricks
Experience with PySpark / Spark
Experience with large-scale customer, product or behavioural datasets
Object-oriented programming experience
Clean code and software design principles
Experience developing modular, reusable and testable ML code
Unit testing experience
Git-based development experience
CI/CD practices for Data Science or ML workloads
Model evaluation and experimentation experience
Experience deploying models into production
Experience monitoring and maintaining production models
Experience with 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 is highly valuable
Several years as a strong hands-on Data Scientist with increasing responsibility for model engineering, deployment and operation
Ability to discuss recommendation methodology and review model performance
Ability to write Python, refactor code, design clean class structures, work in Databricks, debug PySpark, write tests and resolve production issues
Ability to explain technical trade-offs to stakeholders
Ability to build credibility with senior client Data Science stakeholders
Ability to operate independently within the client team
Clear communication of progress, risks and technical decisions
Collaborative approach and good engineering practice

Benefits

Comp & perks

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