Efficus, Inc.
ML Data Scientist | HYBRID - Plano, TX
Efficus, Inc., Plano, Texas, us, 75086
Work Location:
HYBRID - Plano, TX
Role OverviewIn this role you will help drive personalized experiences for customers as a Client Engineer monitoring pipelines batch and ondemand job types to improve Pricing RecommendationsWe are seeking an Client Engineer to play a pivotal role in shaping the future of our consumer journey through cutting edge Machine Learning Client solutions for pricing and recommendationsAbout The Role
Ability to attend meetings and discussions during overlapping XXXX Standard Time XST hours musthaveClient acumen to conceptualize design and implement stateoftheart Client models for dynamic pricing strategies and personalized product recommendationsStrong grasp of understanding difference between data pipelines and Client pipelinesDevelop implement and deploy machine learning models that leverage our unique combination of user behavior and subscription data to improve consumer value from our productsEngineer and maintain largescale consumer behavioral feature stores while ensuring scalability and performanceDevelop and maintain data pipelines and infrastructure to support efficient and scalable Client model development and deploymentCollaborate with crossfunctional teams Marketing Product Sales to ensure your solutions align with strategic objectives and deliver realworld impactCreate algorithms for optimizing consumer journeys and increasing conversion and monetizationDesign analyze and troubleshoot controlled experiments Causal AB tests Multivariate tests to validate your solutions and measure their effectivenessAgile development mindset appreciating the benefit of constant iteration and improvementFocus on business practicality and the 8020 rule very high bar for output quality but recognize the business benefit of having something now vs perfection sometime in the futureAbout You
Bachelors degree in Computer Science or related fields Master or PhD in Machine Learning Statistics Data Science or related quantitative fields preferred5 years of experience in one or more of the following areas machine learning engineering including deep learning recommendation systems pattern recognition data mining or artificial intelligenceProficient in Python SQL intermediate data engineering skill set with tools libraries or frameworks such as MapReduce Hadoop Spark Hive and Big Data technologies scikitlearn Keras TensorFlow PyTorch PySpark etcExperience in Databricks is preferredExperience with various Client techniques and frameworks eg data discretization normalization sampling linear regression decision trees deep neural networks etcExperience in building industrystandard recommender systems and pricing modelsExperience in MLOps Client Engineering and Solution DesignIts Great But Not Required If You Also HaveExperience working in a consumer or B2C space for a SaaS productsoftware providerExperience in developing recommendation systems and deep learningbased modelsExcel in solving ambiguous and complex problems being able to navigate through uncertain situations breaking down complex challenges into manageable components and developing innovative solutions
HYBRID - Plano, TX
Role OverviewIn this role you will help drive personalized experiences for customers as a Client Engineer monitoring pipelines batch and ondemand job types to improve Pricing RecommendationsWe are seeking an Client Engineer to play a pivotal role in shaping the future of our consumer journey through cutting edge Machine Learning Client solutions for pricing and recommendationsAbout The Role
Ability to attend meetings and discussions during overlapping XXXX Standard Time XST hours musthaveClient acumen to conceptualize design and implement stateoftheart Client models for dynamic pricing strategies and personalized product recommendationsStrong grasp of understanding difference between data pipelines and Client pipelinesDevelop implement and deploy machine learning models that leverage our unique combination of user behavior and subscription data to improve consumer value from our productsEngineer and maintain largescale consumer behavioral feature stores while ensuring scalability and performanceDevelop and maintain data pipelines and infrastructure to support efficient and scalable Client model development and deploymentCollaborate with crossfunctional teams Marketing Product Sales to ensure your solutions align with strategic objectives and deliver realworld impactCreate algorithms for optimizing consumer journeys and increasing conversion and monetizationDesign analyze and troubleshoot controlled experiments Causal AB tests Multivariate tests to validate your solutions and measure their effectivenessAgile development mindset appreciating the benefit of constant iteration and improvementFocus on business practicality and the 8020 rule very high bar for output quality but recognize the business benefit of having something now vs perfection sometime in the futureAbout You
Bachelors degree in Computer Science or related fields Master or PhD in Machine Learning Statistics Data Science or related quantitative fields preferred5 years of experience in one or more of the following areas machine learning engineering including deep learning recommendation systems pattern recognition data mining or artificial intelligenceProficient in Python SQL intermediate data engineering skill set with tools libraries or frameworks such as MapReduce Hadoop Spark Hive and Big Data technologies scikitlearn Keras TensorFlow PyTorch PySpark etcExperience in Databricks is preferredExperience with various Client techniques and frameworks eg data discretization normalization sampling linear regression decision trees deep neural networks etcExperience in building industrystandard recommender systems and pricing modelsExperience in MLOps Client Engineering and Solution DesignIts Great But Not Required If You Also HaveExperience working in a consumer or B2C space for a SaaS productsoftware providerExperience in developing recommendation systems and deep learningbased modelsExcel in solving ambiguous and complex problems being able to navigate through uncertain situations breaking down complex challenges into manageable components and developing innovative solutions