Machine Learning Engineer
AGS, LLC
Duluth, United States of America
yesterday
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
EnglishJob location
Duluth, United States of America
Tech stack
Clickstream
Cluster Analysis
Machine Learning
Azure
Spark
Scikit Learn
Statistics Packages
XGBoost
Machine Learning Operations
Job description
- Buildplayersessionbehavioralmodelsretentionprediction,abandonmentmodeling,post-bonusbehavioranalysis,andbetescalationmodelingfromiGamingsessiondata
- DevelopgameperformancepredictionmodelspredictWPUPD,timeondevice,andfloorlongevityfromgamespecificationfeaturesandhistoricalperformancedata,usingagamefeatureextractionpipelinethatreverse-engineersexistingtitlesintostructured,reusablefeatures
- Buildmathmodeloptimizationanalyticsanalyzeactualvs.theoreticalRTP,hitfrequency,andbonusfrequency;identifymathmodelanomaliesacrossthedeployedfleet
- Createplayersegmentationmodelsclusterplayersintobehavioralarchetypes(bonushunters,jackpotchasers,basegamegrinders)toinformgamedesignandoperatorrecommendations
- SupporttheInteractiveYieldMaxyield-managementtoolbuildtheunderlyingmodelsthatpredictwhichAGSgamemaximizesperformanceinagivenfloorposition,operatorproperty,andplayerdemographic
- Buildpredictivemaintenancemodelsanalyzecabineterrorlogsand,assensor/telemetrypipelinesmature(DynamicsFieldService/Dataverse),incorporatetelemetrytoidentifyfailureprecursorpatternsandpredictcomponentfailures
- Feedgamedesigndecisionstranslatemodeloutputsintogamedesigner-friendlyinsightsthatareactionableinthegamespecificationprocess
- DesignandanalyzeA/Btestsexperimentaldesign,statisticalanalysis,andresultsinterpretationforgamemathvarianttesting(whereregulatorilypermitted)
- ProductionalizemodelspackagemodelsfordeploymentonAzureML/Fabric,withMLflow-basedregistry,monitoring,andretrainingpipelines
Requirements
- 48 years of data science and/or ML engineering experience, with demonstrated production model deployment (not just notebook analysis)
- Behavioralanalyticsexpertisehasbuiltretention,churn,orengagementmodelsusingevent-levelbehavioraldata(sessionlogs,clickstreams,transactionsequences)
- StrongPythonandSQLskillspandas,scikit-learn,XGBoost,statsmodels;canquerythedatawarehouseindependently(amixofon-premSQLServerandSalesforcetoday,migratingtoMicrosoftFabric/OneLake)withoutrelyingonadataengineerforeveryanalysis
- Statisticalrigorsurvivalanalysis,A/Btestdesign,causalinference,regressionmodeling;understandsthedifferencebetweencorrelationandcausation
- Machinelearningbreadthclassification,regression,clustering,recommendationsystems;canselecttherightmodelingapproachforeachproblem
- Datacommunicationskillscantranslatemodeloutputsintobusiness-friendlylanguagethatgamedesignersandcommercialleaderscanacton
- Experiencewithmessy,real-worlddatacomfortablewheregamefeaturesaren'tfullydocumentedandpipelinesarestillbeingbuilt;doesn'trequireperfectdatatodelivervalue
- Bachelor'sorMaster'sdegreeinDataScience,Statistics,ComputerScience,Mathematics,orrelatedquantitativefield
Preferred
- Gaming,mobilegaming,orconsumerbehavioralanalyticsexperience
- FamiliaritywithcasinogamemechanicsRTP,volatility,Hold&Spin,theoindex
- ExperiencewithtimeseriesanalysisandanomalydetectionforIoT/sensordata
- Knowledgeofresponsiblegamblingdataconsiderations
- Experience with MLflow, Azure ML, or Fabric Notebooks/Spark for model lifecycle management