Impact.com

Impact.com

Sr. Data Scientist, Programmatic Algorithms

Seattle, WA · Senior · Contract

Sponsorship not specified$165k-$185kDetected 85 days ago
PythonFull-Stack DevelopmentAlgorithmsSQLBigQueryDatabricksGCPPlatform EngineeringRESTgRPCKafkaMachine LearningTensorFlowPyTorchscikit-learnSparkData EngineeringData ScienceMLOpsStatisticsA/B TestingPerformance MarketingForecastingInventory Management

About the role

  • As consumers increasingly rely on recommendations from people and communities they trust, impact.com helps brands show up where it matters most.
  • Your Role at impact.com: We're seeking a Senior Data Scientist to serve as an embedded Data Scientist within our Programmatic Experience Group.
  • This is a high-craft, high-ownership individual contributor role.

Responsibilities

  • Design and deploy ML models that optimize auction pricing, bid shading, floor price setting, and yield across Impact's programmatic inventory.
  • Develop and maintain feedback loops that allow pricing models to adapt to shifting market conditions, inventory mix, and demand patterns.
  • communicate tradeoffs between yield maximization, fill rate, and partner ROI to stakeholders.
  • Own ML-driven inventory allocation logic: routing, pacing, and matching supply to demand across partner segments, deal types, and campaign objectives.
  • Build models that forecast inventory availability, demand curves, and clearing prices to support proactive allocation decisions.
  • Design and own the data infrastructure that feeds programmatic models: event pipelines, feature stores, training datasets, and real-time feature serving.
  • Build robust data pipelines with production-grade standards: reliability, observability, versioning, and efficient reprocessing.
  • Quantify the revenue impact of pricing model improvements; communicate tradeoffs between yield maximization, fill rate, and partner ROI to stakeholders.
  • Deploy models to production real-time inference environments; own latency, reliability, and throughput requirements for auction-time decision-making.
  • Partner with MLOps and Platform Engineering to ensure scalable, low-latency serving infrastructure meets SLOs under high-volume auction traffic.

Requirements

  • Production ML engineering: Proven ability to take models from prototype to production independently - including real-time inference, monitoring, retraining pipelines, and SLO ownership.
  • proficiency with ML libraries (scikit-learn, XGBoost, LightGBM, PyTorch/TensorFlow) and large-scale data tools (Spark, Kafka, or equivalent streaming/batch frameworks).
  • Communication: Ability to explain complex modeling decisions and tradeoffs to Product and business stakeholders
  • Proven ability to take models from prototype to production independently - including real-time inference, monitoring, retraining pipelines, and SLO ownership.
  • Required
  • Programmatic & marketplace depth: Demonstrated understanding of programmatic auction mechanics (RTB, header bidding, floor pricing, deal types, bid shading) and how ML can be applied to optimize outcomes across the supply-demand stack.
  • Data architecture: Experience designing and building data pipelines, feature stores, and training infrastructure for high-volume, low-latency ML systems.
  • Technical skills:
  • Strong Python and SQL
  • Experimentation rigor: Strong grasp of causal inference and experiment design in online, delayed-feedback environments (auction holdouts, switchback tests, variance reduction techniques).
  • comfortable presenting in cross-functional forums.

Nice to have

  • Direct experience with SSP, DSP, or exchange-side yield optimization - particularly floor price optimization, bid landscape modeling, or deal matching algorithms.
  • Familiarity with auction theory (first-price vs. second-price dynamics, optimal reserve pricing, revenue equivalence) and its practical implications for programmatic ML.
  • Experience with GCP tools (BigQuery, Vertex AI, Dataflow, Pub/Sub) and/or Databricks/Spark for large-scale event processing and model training.
  • Familiarity with Impact's affiliate and partnership ecosystem, or prior experience at the intersection of performance marketing and programmatic delivery.
  • Marketplace intuition.
  • You understand programmatic auctions not just as an engineer but as an economist - you think about incentive structures, equilibrium dynamics, and how model decisions ripple through the supply-demand stack.
  • Full-stack ML ownership.
  • You're as comfortable designing a feature store schema as you are tuning a gradient boosting model or debugging a latency spike in production.

Skills

  • Experience with real-time feature serving and low-latency model deployment (REST APIs, gRPC, or streaming inference).
  • Familiarity with production ML workflows: model versioning, drift monitoring, A/B testing, evaluation, and retraining.
  • Experience processing and modeling at programmatic data scale: high-cardinality auction logs, bid stream data, impression and click events.
  • Education: Bachelor's in a quantitative field (CS, Statistics, Math, Engineering, Economics, or similar); Master's/PhD preferred.
  • Preferred / Nice to Have
  • Experience with contextual bandits, multi-armed bandits, or reinforcement learning applied to real-time decisioning problems.
  • Knowledge of online learning and adaptive algorithms in production environments with non-stationary data distributions.
  • Exposure to supply forecasting, inventory management, or capacity planning in programmatic or marketplace contexts.
  • What Sets You Apart
  • Translate experimental results into clear business narratives; present findings and recommendations to Product and business stakeholders.

Compensation

  • $165,000 - $185,000 per year, plus an additional 5% variable annual bonus contingent on Company performance and eligible to receive a Restricted Stock Unit (RSU) grant.
  • This is the pay range the Company believes is equitable for this position at the time of this posting.
  • Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time.
  • Our mental health and wellness benefit includes up to 12 fully covered therapy/coaching sessions per year, with additional dependent coverage.
  • A Stake in Our Growth: We offer Restricted Stock Units (RSUs) as part of our total compensation, giving you a stake in the company's growth with a 3-year vesting schedule, pending Board approval.

Benefits

  • Medical, Dental, and Vision insurance
  • Flexible spending accounts and 401(k)
  • That's why we've built a benefits package that supports your well-being, growth, and work-life balance.
  • Flexible Working: Our Responsible PTO policy means you can take the time off you need to rest and recharge.
  • We're committed to a positive work-life balance and provide a flexible environment that allows you to be happy and fulfilled in both your career and your personal life.
  • Health and Wellness: Your well-being is a priority.
  • Our mental health and wellness benefit includes up to 12 fully covered therapy/coaching sessions per year, with additional dependent coverage.
  • A Stake in Our Growth: We offer Restricted Stock Units (RSUs) as part of our total compensation, giving you a stake in the company's growth with a 3-year vesting schedule, pending Board approval.
  • Build monitoring systems that track model performance, data drift, and system health in production; define alerting thresholds and retraining triggers.

Company info

  • At impact.com, we believe that when you're happy and fulfilled, you do your best work.
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