{"id":73544,"url":"https://alion.io/job/impact-com-sr-data-scientist-programmatic-algorithms-3","title":"Sr. Data Scientist, Programmatic Algorithms","company":{"id":5431,"name":"impact.com","domain":"impact.com","url":"https://alion.io/company/impact-com","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":80,"open_postings":23,"ghost_share":0,"stale_share":0.609,"repost_share":0,"time_to_fill_p50_days":76,"computed_at":"2026-10-16T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Vancouver, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":165000,"max":185000,"currency":"USD","period":"year","gross":null,"usd_annual":185000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Apache Kafka","optional":false},{"name":"Feature Store","optional":false},{"name":"gRPC","optional":false},{"name":"LightGBM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Rest API","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"XGBoost","optional":false},{"name":"BigQuery","optional":true},{"name":"Databricks","optional":true},{"name":"Federated Learning","optional":true},{"name":"GCP","optional":true},{"name":"Google BigQuery","optional":true},{"name":"Vertex AI","optional":true}],"status":"live","first_seen_at":"2026-04-27T21:09:29Z","employer_posted_date":"2026-09-10","last_verified_at":"2026-10-17T01:11:38Z","board_verified":true,"closed_at":null,"days_open":172,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":171},"description":"About impact.com:\nimpact.com is the world’s leading commerce partnership marketing platform, transforming the way businesses grow by enabling them to discover, manage, and scale partnerships across the entire customer journey. From affiliates and influencers to content publishers, brand ambassadors, and customer advocates, impact.com empowers brands to drive trusted, performance-based growth through authentic relationships. Its award-winning products - Performance (affiliate), Creator (influencer), and Advocate (customer referral) - unify every type of partner into one integrated platform. As consumers increasingly rely on recommendations from people and communities they trust, impact.com helps brands show up where it matters most. Today, over 5,000 global brands - including Walmart, Uber, Shopify, Lenovo, L’Oréal, and Fanatics - rely on impact.com to power more than 350,000 partnerships that deliver measurable business results.\nYour Role atimpact.com:\nWe're seeking a Senior Data Scientist to serve as an embedded Data Scientist within our Programmatic Experience Group. You'll own the design and deployment of machine learning models that optimize yield, pricing, and inventory allocation at scale - sitting at the intersection of data science, platform engineering, and marketplace economics.\nThis is a high-craft, high-ownership individual contributor role. You'll work end-to-end: architecting the data pipelines that feed your models, engineering the features that drive performance, and deploying real-time inference systems that make decisions at speed. Your work directly determines how effectively Impact's programmatic marketplace balances advertiser performance with publisher monetization - making this one of the highest-leverage technical roles in the business.\nYou'll collaborate closely with Product, Data Science, and Programmatic Delivery Engine Engineering, but you operate with significant autonomy. You're expected to bring both the modeling rigor of a data scientist and the production instincts of an ML engineer - and to be genuinely excited about both.\nWhat You'll Do:\nYield Optimization & Pricing Models\nDesign and deploy ML models that optimize auction pricing, bid shading, floor price setting, and yield across Impact's programmatic inventory.\nBuild and iterate on real-time pricing algorithms that balance short-term revenue efficiency with long-term publisher and advertiser health.\nDevelop and maintain feedback loops that allow pricing models to adapt to shifting market conditions, inventory mix, and demand patterns.\nQuantify the revenue impact of pricing model improvements; communicate tradeoffs between yield maximization, fill rate, and partner ROI to stakeholders.\nInventory Allocation & Supply Optimization\nOwn ML-driven inventory allocation logic: routing, pacing, and matching supply to demand across partner segments, deal types, and campaign objectives.\nBuild models that forecast inventory availability, demand curves, and clearing prices to support proactive allocation decisions.\nIdentify and address inefficiencies in inventory utilization - including unsold inventory, suboptimal deal matching, and allocation imbalances across the publisher base.\nData Architecture & Feature Engineering\nDesign and own the data infrastructure that feeds programmatic models: event pipelines, feature stores, training datasets, and real-time feature serving.\nEngineer high-signal features from auction logs, bid stream data, user signals, contextual attributes, and historical performance - at the scale of programmatic data volumes.\nBuild robust data pipelines with production-grade standards: reliability, observability, versioning, and efficient reprocessing.\nReal-Time Inference & Production ML\nDeploy models to production real-time inference environments; own latency, reliability, and throughput requirements for auction-time decision-making.\nBuild monitoring systems that track model performance, data drift, and system health in production; define alerting thresholds and retraining triggers.\nPartner with MLOps and Platform Engineering to ensure scalable, low-latency serving infrastructure meets SLOs under high-volume auction traffic.\nOwn the full model lifecycle: training, evaluation, deployment, A/B testing, and iteration.\nExperimentation & Performance Measurement\nDesign and execute rigorous A/B and holdout experiments to measure the causal impact of model changes on yield, fill rate, advertiser performance, and publisher revenue.\nBuild evaluation frameworks that go beyond offline metrics - validating model behavior in live auction environments where feedback signals are delayed or noisy.\nTranslate experimental results into clear business narratives; present findings and recommendations to Product and business stakeholders.\nSelf-Learning Systems & Feedback Loops\nResearch and implement adaptive, self-learning components within the programmatic stack - including contextual bandits, reinforcement learning signals, and online learning approaches where appropriate.\nDesign feedback mechanisms that close the loop between auction outcomes, model updates, and system behavior; reduce reliance on manual tuning and rule-based overrides.\nStay current with advances in programmatic ML, auction theory, and online optimization; evaluate applicability to Impact's specific marketplace dynamics.\nCross-Functional Collaboration\nServe as the primary ML technical partner for the Rubicon product and engineering teams; translate business requirements into modeling approaches and communicate technical tradeoffs clearly.\nCollaborate with Data Science peers on shared infrastructure, modeling standards, and cross-domain feature reuse.\nDocument models, architectures, and experimental findings to a standard that enables review, replication, and knowledge transfer across teams.\nWhat You Bring:\nRequired\n Experience: 5+ years in data science, ML engineering, or quantitative research, with at least 2+ years building and deploying ML models in programmatic advertising, ad tech, marketplace optimization, or a closely related domain (e.g., real-time bidding, dynamic pricing, auction systems).\n 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.\nProduction ML engineering: Proven ability to take models from prototype to production independently - including real-time inference, monitoring, retraining pipelines, and SLO ownership.\nData architecture: Experience designing and building data pipelines, feature stores, and training infrastructure for high-volume, low-latency ML systems.\n Technical skills:\nStrong Python and SQL; proficiency with ML libraries (scikit-learn, XGBoost, LightGBM, PyTorch/TensorFlow) and large-scale data tools (Spark, Kafka, or equivalent streaming/batch frameworks).\nExperience with real-time feature serving and low-latency model deployment (REST APIs, gRPC, or streaming inference).\nFamiliarity with production ML workflows: model versioning, drift monitoring, A/B testing, evaluation, and retraining.\nExperience processing and modeling at programmatic data scale: high-cardinality auction logs, bid stream data, impression and click events.\n Experimentation rigor: Strong grasp of causal inference and experiment design in online, delayed-feedback environments (auction holdouts, switchback tests, variance reduction techniques).\nCommunication: Ability to explain complex modeling decisions and tradeoffs to Product and business stakeholders; comfortable presenting in cross-functional forums.\n Education: Bachelor's in a quantitative field (CS, Statistics, Math, Engineering, Economics, or similar); Master's/PhD preferred.\nPreferred / Nice to Have\nDirect experience with SSP, DSP, or exchange-side yield optimization - particularly floor price optimization, bid landscape modeling, or deal matching algorithms.\nFamiliarity with auction theory (first-price vs. second-price dynamics, optimal reserve pricing, revenue equivalence) and its practical implications for programmatic ML.\nExperience with contextual bandits, multi-armed bandits, or reinforcement learning applied to real-time decisioning problems.\nKnowledge of online learning and adaptive algorithms in production environments with non-stationary data distributions.\nFamiliarity with privacy-preserving ML techniques relevant to programmatic (differential privacy, federated learning, cookieless attribution modeling).\nExperience with GCP tools (BigQuery, Vertex AI, Dataflow, Pub/Sub) and/or Databricks/Spark for large-scale event processing and model training.\nExposure to supply forecasting, inventory management, or capacity planning in programmatic or marketplace contexts.\nFamiliarity with Impact's affiliate and partnership ecosystem, or prior experience at the intersection of performance marketing and programmatic delivery.\nWhat Sets You Apart\nMarketplace 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.\nFull-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. You own the whole chain.\nFeedback loop thinking. You don't just deploy models - you design the systems that make them smarter over time. You think about how today's decisions become tomorrow's training signal.\nRigor under real-world constraints. You know how to run clean experiments in environments where feedback is delayed, data is noisy, and business pressures create tradeoffs. You don't let imperfect conditions become an excuse for imprecise thinking.\nPragmatic delivery. You ship. You balance the perfect with the production-ready, iterate fast, and know when an MVP outperforms a six-month research project.\nCollaborative depth. You build genuine technical trust with engineering and product partners - not just by having good ideas, but by following through, communicating clearly, and making the integration easy.\nSalary Range: $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.\n*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.\nBenefits and Perks: \nAt impact.com, we believe that when you’re happy and fulfilled, you do your best work. That’s why we’ve built a benefits package that supports your well-being, growth, and work-life balance.\nStrong extended health benefits: Health & Prescription coverage, vision and dental care, virtual health care, out-of-country medical coverage\nInsurance coverage (life, short-term disability, long-term disability, and more)\nHealth Care Spending Account\nTwo different Employee Assistance Programs\nFlexible 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.\nHealth 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. We also offer a monthly gym reimbursement policy to support your physical health.\nA 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 Boar...","description_format":"text","description_chars":13138,"description_truncated":true,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Continuous learning","Flexible schedule","Home office","Insurance coverage","Parental leave","Restricted stock units"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Influencer Marketing","Marketing Analytics & Attribution","Digital Marketing"],"lifecycle":[{"event":"open","at":"2026-04-27T21:09:29Z"}],"visa":[],"liveness":{"score":7,"band":"cold","label":"Long shot","p_open":1,"p_active":0.265,"p_room":0.28,"age_days":171,"expected_fill_days":76,"reasons":["conf:2","stale_co","evergreen","velocity","win:tail","crowd:"],"computed_at":"2026-10-16T05:45:00Z"},"pay":{"stated_usd_annual":185000,"is_top_pay":true},"html_url":"https://alion.io/job/impact-com-sr-data-scientist-programmatic-algorithms-3","json_url":"https://alion.io/job/impact-com-sr-data-scientist-programmatic-algorithms-3.json","meta":{"generated_at":"2026-10-17T04:55:35Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":6421,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-18T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":5431},"rest":"https://alion.io/mcp/rest/get_company?id=5431"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fimpact-com-sr-data-scientist-programmatic-algorithms-3"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fimpact-com-sr-data-scientist-programmatic-algorithms-3"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fimpact-com-sr-data-scientist-programmatic-algorithms-3"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/impact-com-sr-data-scientist-programmatic-algorithms-3\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fimpact-com-sr-data-scientist-programmatic-algorithms-3"}]}