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Senior Applied Scientist [Incentives]

CyprusRelocationHybridSenior

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.

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

InDrive

inDrive is a mobility platform that operates in over 888 cities across 48 countries, with a focus on fair pricing and a peer-to-peer model.

Ride-hailing app where passengers can find rides, set their price, and choose their driver, and where drivers can offer their services and negotiate fares.

See all 15 jobs at InDrive

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