Senior Applied Scientist (Researcher) - Incentives
inDrive
Poland
Posted on Apr 23, 2026
We are looking for an expert who will develop and automate decision-making algorithms in the area of incentives. Your core focus will be to design and deploy adaptive data-driven mechanisms that determine which goal to set for which user, and what reward to offer, in order to maximize the incremental effect for every dollar invested.
- Department
- Analytics Department
- Employment Type
- Full Time
- Location
- Cyprus
- Address
- Limassol, Limassol
- Workplace type
- Hybrid
Key Responsibilities
- Intervention Algorithm Automation: Design and implement incentive management systems as closed-loop feedback control systems to continuously optimize budget efficiency and marketplace balance
- Incremental Impact Maximization (Uplift Modeling): Create and advance causal inference and uplift models (e.g., meta-learners) to evaluate the true incremental value of rewards and target personalized offers
- Behavioral Modeling & Business Impact: Research and model the non-linear responses of marketplace participants to changing conditions (prices, incentive terms), translating these insights into algorithmic strategies that drive user retention and lifetime value (LTV)
- End-to-End Development (Research-to-Production): Translate research models into production-grade code, developing modular frameworks and monitoring systems to ensure algorithms operate reliably in real time
- Cross-Functional Leadership: Act as a strategic partner to product managers and engineers, driving the product roadmap through data-driven storytelling and aligning complex algorithmic solutions with overarching business goals
Skills, Knowledge and Expertise
- 3+ years of experience in Data Analytics, Data Science, Applied Research, or algorithmic product optimization, preferably within a dynamic incentive-driven environment
- Strong analytical mindset with expertise in Machine Learning, behavioral modeling, and causal inference
- Solid foundation in mathematics and economics, including knowledge of elasticity models, incentive response dynamics, and retention analytics
- Advanced SQL and Python proficiency, with experience working with large datasets and the ability to translate research models into production-grade decision logic
- Advanced Experimentation: Experience with A/B testing frameworks, switchback experiments, and evaluating causal effects in networked systems with feedback loops
- Strong communication and stakeholder management skills, with the ability to collaborate closely with engineering teams and influence product decision-making
- Professional working proficiency in English
- Nice to have: Experience formulating budget allocation tasks as linear, integer, or mixed-integer optimization problems to find the optimal balance between costs and desired outcomes
- Nice to have: Experience with Uplift Modeling — Proven ability to evaluate causal effects, build propensity/response models, and design targeted interventions
Conditions
- Stable salary, official employment
- Health insurance
- Hybrid work mode and flexible schedule
- Access to professional counseling services, including psychological, financial, and legal support
- Discount club membership
- Diverse internal training programs
- Partially or fully paid additional training courses
- All necessary work equipment
About inDrive
inDrive is a global tech company on a mission to challenge injustice. We started in 2012 in the coldest city on Earth, when a group of friends created a way for people to agree on fair ride prices. That idea grew into one of the world’s top ride-hailing apps, now with 360M installs across 48 countries.
Today, we offer more than rides: from freight and delivery to intercity travel and financial services, all designed to put people first. Our goal is to positively impact 1 billion lives by 2030. Through inVision, our non-profit arm, we support education, entrepreneurship, and equality in underserved communities.
Ready to ignite your inner drive?
Our Hiring Process
Stage 1:
Applied
Stage 2:
Interview with Talent Acquisition
Stage 3:
Technical Scoring
Stage 4:
Third Interview
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