At BESTSECRET, we are building a next-generation profit optimization engine that determines how we buy, price, and present our products. Our mission is to design and own the system that drives business outcomes by orchestrating pricing, buying, and product visibility into one coherent, profit-maximizing decision engine. We turn data into a strategic advantage by combining advanced modeling, real-time decisioning, and strong business ownership to maximize revenue and efficiency.
We are looking for a Director of Data Science, Profit Optimization (all genders) who combines deep technical expertise with strong ownership and leadership. This is a hands-on role for someone who enjoys building and solving complex business problems while guiding a team and shaping how the business maximizes profit.
Key Responsibilities
Own the strategy, roadmap, and execution of the profit optimization engine across pricing, buying, and product visibility that maximizes profit and business performance
Design, build, and operate scalable, production-grade systems that translate business logic into pricing, buying, and product visibility decisions
Develop the joint objective function across pricing, buying, and product visibility and translate complex business trade-offs into formal models and decision rules (eg margin vs. growth, customer satisfaction vs. sell-through, short- vs. long-term performance)
Develop and evolve advanced demand forecasting and optimization models, moving from heuristic approaches to scalable, data-driven systems where it has the highest impact
Work hands-on on the hardest analytical and modeling challenges, especially where models meet real-world constraints and imperfect data
Own end-to-end solution impact, including defining success metrics, running experiments, and ensuring measurable business outcomes
Align and coordinate initiatives across teams, acting as the central counterpart for leadership as well as buying, pricing, and product teams on profit steering topics
Lead and grow a high-impact data science team
Requirements
Advanced degree in Data Science, Economics, Statistics, Computer Science, or a related quantitative field (PhD is a plus)
Proven track record of building or owning decision systems that directly drive business outcomes (eg pricing engines, revenue management, marketplace optimization), ideally in complex, high-SKU or fast-moving environments such as e-commerce, retail, travel, or marketplaces
Strong expertise in machine learning, statistical modeling, optimization, and data-driven decision-making, with the ability to translate business problems into objective functions, constraints, and scalable decision logic
Ability to operate across abstraction levels, from strategy and solution design to hands-on modeling and implementation, with experience deploying end-to-end solutions into production (eg using Python, SQL , AzureML and ML modules such as LGBM, XGBoost or Tensorflow Recommenders ).
Hands-on, ownership-driven mindset with strong leadership, stakeholder management, and communication skills, and a proven ability to drive outcomes in cross-functional environments
Fluency in English; German is a plus
What makes this role different
This role focuses on shaping the system that determines how the business allocates capital, inventory, and customer attention, rather than optimizing a single model or metric
Ownership extends beyond implementation to defining the underlying logic, including defining what 'optimal' means and making trade-offs explicit and actionable in collaboration with stakeholders.
The work centers on complex, real-world problems where clean solutions rarely exist, and impact comes from making better decisions under uncertainty rather than building perfect models
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