# Senior Applied Researcher — Incentives at Indrive

> Hybrid · Cyprus · Senior · Other · open. Source: https://alderhq.app/jobs/pinpoint%3Aindrive%3A606160 (read 2026-11-08).

## Facts (observed)

- Company: [Indrive](https://alderhq.app/companies/indrive)
- Location text: Cyprus, Limassol
- Where it can be done from (inferred): Hybrid · Cyprus (evidence: "Location: Cyprus, Limassol")
- Posted: already open when tracking began; date unknown
- First seen by alder: 2026-11-04 · last verified: 2026-11-07
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://indrive.pinpointhq.com/en/postings/dff46675-b8e7-421c-ba7c-56029ab0cba1
- Skills listed (inferred): Python, SQL

## Pay and sponsorship

- Posted pay: €71k per year (from the description)

## Description (the employer's text)

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.

### 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

- Professional 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.
### Benefits

- Help us challenge injustice by creating fair choices for millions of people across in 47 countries
- Develop your professional skills with access to mentoring, career consulting, and learning programs
- Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program
- Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects
- Work alongside people who take initiative, speak openly, and challenge themselves to grow
- Improve your language skills through co-financed courses and internal speaking clubs
- Annual salary from EUR 70 700 gross
Final benefits may vary depending on the location.

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/pinpoint%3Aindrive%3A606160 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.