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What we're looking for
- Commercial experience with classical data science and ML models
- Solid knowledge of customer analytics or advanced forecasting
- Model hyperparameter tuning and validation frameworks
- Experience with business requirements gathering and technical planning
- Fluency in Python and basic working knowledge of SQL
About the role
ABOUT THE ROLE
Our Data Science and AI team delivers machine learning solutions for global clients, with a particular focus on forecasting, customer analytics, and causality frameworks. Projects span next best offer and action modelling, propensity and churn modelling, demand and sales forecasting, and revenue growth management.
As Lead Data Scientist, you will take ownership of delivery across end-to-end classification and forecasting use cases — setting technical direction, driving quality, and ensuring the team produces work that connects directly to business outcomes. You will be the senior technical voice in client engagements, leading requirements gathering, shaping solution approaches, and supporting pre-sales activity. Alongside delivery, you will mentor other data scientists and be expected to raise the standard of the practice around you.
WHAT YOU'LL WORK ON
Technical leadership across use cases
Own end-to-end delivery of classification and forecasting projects — from problem framing and data preparation through model development, evaluation, and deployment support. Set the technical direction and hold the bar on quality.
Data exploration and quality
Lead exploratory data analysis on tabular and time-series data, identify quality issues, and define feature engineering approaches that feed production models.
Model development and validation
Train, tune, and validate ML models — logistic regression, tree-based models, gradient boosting, simple neural networks, and classical time-series models — with clear evaluation frameworks tied to business KPIs.
Stakeholder engagement
Lead business requirements gathering, define success metrics, assess data feasibility, and manage stakeholder expectations at senior level. Build clear visualisations and concise reports to communicate model results.
Production collaboration
Work with data engineers and AI engineers to bring models into production — batch scoring, APIs, model monitoring, and dashboards — ensuring handoffs are clean and well-documented.
Documentation and reproducibility
Set standards for documenting data sources, modelling assumptions, and experiment results across notebooks, reports, and wikis.
Mentorship and pre-sales
Mentor other data scientists, raise practice standards, and contribute to pre-sales activities including scoping, estimation, and solution design for prospective clients.
WHAT WE LOOK FOR
Strong classical data science and ML background
Extensive commercial experience across the full ML workflow, with a track record of delivering production systems that drive measurable business impact.
Customer analytics or advanced forecasting expertise
Deep hands-on experience in customer analytics (propensity, churn, next best action) or advanced forecasting (demand, sales). Familiarity with causality frameworks is a strong advantage.
Hyperparameter tuning and validation frameworks
Expert knowledge of model tuning approaches and validation frameworks, with a clear understanding of how metric choices connect to business outcomes.
Business requirements and technical planning
Proven ability to lead requirements gathering with non-technical stakeholders, define success metrics, and translate ambiguous business problems into well-scoped technical plans.
Python and SQL
Fluent in Python for data science and modelling work. Solid working knowledge of SQL for data access, exploration, and pipeline work.
THE TEAM
You'll join a specialist Data Science and AI practice working alongside experienced consultants, ML engineers, and data engineers. The team delivers solutions for large international clients across CPG, retail, and manufacturing. There is a strong knowledge-sharing culture, with internal communities, competency centres, and structured learning programmes built into how the team operates.
COMPENSATION & BENEFITS
Rate
140 – 150 PLN per hour on a B2B contract, depending on experience.
Contract flexibility
Flexibility on working hours and preferred form of contract.
Workation policy
Option to work remotely from other locations for defined periods.
Onboarding
Comprehensive online onboarding programme with a dedicated buddy from day one.
Learning and development
Unlimited access to the Udemy learning platform from day one. Certificate training programmes, upskilling support, capability development programmes, competency centres, knowledge sharing sessions, community webinars, and over 110 training opportunities per year.
Career growth
Internal promotion pathways — 76% of managers were promoted internally. Cooperation with top-tier engineers and domain experts across the organisation.
Referral bonuses
Financial rewards for successful employee referrals.
Wellbeing
Activities to support health and wellbeing, with opportunities to contribute to charitable causes and environmental initiatives.
Employer recognition
Great Place to Work certified employer.
Our Data Science and AI team delivers machine learning solutions for global clients, with a particular focus on forecasting, customer analytics, and causality frameworks. Projects span next best offer and action modelling, propensity and churn modelling, demand and sales forecasting, and revenue growth management.
As Lead Data Scientist, you will take ownership of delivery across end-to-end classification and forecasting use cases — setting technical direction, driving quality, and ensuring the team produces work that connects directly to business outcomes. You will be the senior technical voice in client engagements, leading requirements gathering, shaping solution approaches, and supporting pre-sales activity. Alongside delivery, you will mentor other data scientists and be expected to raise the standard of the practice around you.
WHAT YOU'LL WORK ON
Technical leadership across use cases
Own end-to-end delivery of classification and forecasting projects — from problem framing and data preparation through model development, evaluation, and deployment support. Set the technical direction and hold the bar on quality.
Data exploration and quality
Lead exploratory data analysis on tabular and time-series data, identify quality issues, and define feature engineering approaches that feed production models.
Model development and validation
Train, tune, and validate ML models — logistic regression, tree-based models, gradient boosting, simple neural networks, and classical time-series models — with clear evaluation frameworks tied to business KPIs.
Stakeholder engagement
Lead business requirements gathering, define success metrics, assess data feasibility, and manage stakeholder expectations at senior level. Build clear visualisations and concise reports to communicate model results.
Production collaboration
Work with data engineers and AI engineers to bring models into production — batch scoring, APIs, model monitoring, and dashboards — ensuring handoffs are clean and well-documented.
Documentation and reproducibility
Set standards for documenting data sources, modelling assumptions, and experiment results across notebooks, reports, and wikis.
Mentorship and pre-sales
Mentor other data scientists, raise practice standards, and contribute to pre-sales activities including scoping, estimation, and solution design for prospective clients.
WHAT WE LOOK FOR
Strong classical data science and ML background
Extensive commercial experience across the full ML workflow, with a track record of delivering production systems that drive measurable business impact.
Customer analytics or advanced forecasting expertise
Deep hands-on experience in customer analytics (propensity, churn, next best action) or advanced forecasting (demand, sales). Familiarity with causality frameworks is a strong advantage.
Hyperparameter tuning and validation frameworks
Expert knowledge of model tuning approaches and validation frameworks, with a clear understanding of how metric choices connect to business outcomes.
Business requirements and technical planning
Proven ability to lead requirements gathering with non-technical stakeholders, define success metrics, and translate ambiguous business problems into well-scoped technical plans.
Python and SQL
Fluent in Python for data science and modelling work. Solid working knowledge of SQL for data access, exploration, and pipeline work.
THE TEAM
You'll join a specialist Data Science and AI practice working alongside experienced consultants, ML engineers, and data engineers. The team delivers solutions for large international clients across CPG, retail, and manufacturing. There is a strong knowledge-sharing culture, with internal communities, competency centres, and structured learning programmes built into how the team operates.
COMPENSATION & BENEFITS
Rate
140 – 150 PLN per hour on a B2B contract, depending on experience.
Contract flexibility
Flexibility on working hours and preferred form of contract.
Workation policy
Option to work remotely from other locations for defined periods.
Onboarding
Comprehensive online onboarding programme with a dedicated buddy from day one.
Learning and development
Unlimited access to the Udemy learning platform from day one. Certificate training programmes, upskilling support, capability development programmes, competency centres, knowledge sharing sessions, community webinars, and over 110 training opportunities per year.
Career growth
Internal promotion pathways — 76% of managers were promoted internally. Cooperation with top-tier engineers and domain experts across the organisation.
Referral bonuses
Financial rewards for successful employee referrals.
Wellbeing
Activities to support health and wellbeing, with opportunities to contribute to charitable causes and environmental initiatives.
Employer recognition
Great Place to Work certified employer.
Compensation & benefits
Stable employment
Workation policy
Great Place to Work® certified employer
Flexibility regarding working hours and preferred form of contract
Comprehensive online onboarding program with a 'Buddy' from day 1
Cooperation with top-tier engineers and experts
Unlimited access to the Udemy learning platform from day 1
Certificate training programs
Upskilling support
Capability development programs
Competency Centers
Knowledge sharing sessions
Community webinars
110+ training opportunities yearly
Internal promotions
Diverse, inclusive, and values-driven community
Autonomy to choose the way you work
Referral bonuses
Activities to support well-being and health
Opportunities to donate to charities and support the environment
Modern office equipment
About Lingaro
An ethical business committed to diversity, equity, and inclusion, ensuring equal opportunities and fostering a safe, respectful workplace. The company believes diversity fuels both personal and business growth and is committed to building an inclusive community where all people thrive regardless of their backgrounds, identities, or other personal characteristics.