Money Fit by DRS
Data Scientist
Money Fit by DRS, Los Angeles, California, United States, 90079
Data Scientist (NYC, LA, SF or Seattle)
Onsite Hybrid role - 3 days a weekWe are seeking a highly motivated and talented Senior Data Scientist to join our team of experts in developing and maintaining recommendation and personalization algorithms for Disney Streaming's suite of streaming video apps. As a member of our team, you will play a pivotal role in shaping the future of our streaming services by applying state-of-the-art machine learning methods to meet strategic product personalization goals.Responsibilities:
Algorithm Development and Maintenance:Utilize cutting-edge machine learning techniques to develop and enhance algorithms for personalization, recommendation, and predictive systems.Take ownership of maintaining and optimizing algorithms deployed in production environments.Serve as the point person for explaining methodologies to both technical and non-technical teams, fostering clear communication.Analysis and Algorithm Optimization:Conduct in-depth analysis of user interactions within our apps and user profiles to drive improvements in key personalization metrics.Collaborate with data scientists and engineers to refine algorithms and enhance their performance continually.MVP Development:Innovate and develop machine learning products that can be used for new production features or by downstream production algorithms.Work closely with cross-functional teams to prototype and operationalize personalization solutions.Development Best Practices:Maintain and establish best practices for algorithm development, testing, and deployment, ensuring high-quality code and efficient processes.Collaboration with Product and Business Stakeholders:Identify and define new personalization opportunities by collaborating with product and business stakeholders.Collaborate with other data teams to improve data collection, experimentation, and analysis methods.Required Qualifications:
7+ years of analytical experience5+ years of experience developing machine learning models and performing data analysis with Python and tensor-based model development frameworks (e.g. PyTorch, Tensorflow)5+ years writing production-level, scalable code (e.g. Python, Scala)5+ years of experience developing algorithms for deployment to production systemsIn-depth understanding of modern machine learning (e.g. deep learning methods), models, and their mathematical underpinnings for recommendation enginesIn-depth understanding of the latest in natural language processing techniques and contextualized word embedding modelsExperience deploying and maintaining pipelines (AWS, Docker, Airflow) and in engineering big-data solutions using technologies like Databricks, S3, and SparkFamiliarity with data exploration and data visualization tools like Tableau, Looker, etc.Understanding of statistical concepts (e.g., hypothesis testing, regression analysis)Ability to gauge the complexity of machine learning problems and a willingness to execute simple approaches for quick, effective solutions as appropriateStrong written and verbal communication skillsAbility to explain how models are used and algorithms behave to both technical and non-technical audiencesAdditional Preferred Qualifications:
MS or PhD in computer science, data science, statistics, math, or related quantitative fieldProduction experience with developing content recommendation algorithms at scaleExperience building and deploying full stack ML pipelines: data extraction, data mining, model training, feature development, testing, and deploymentExperience with graph-based data workflows such as Apache AirflowExperience engineering big-data solutions using technologies like EMR, S3, Spark, DatabricksFamiliar with metadata management, data lineage, and principles of data governanceExperience loading and querying cloud-hosted databases such as SnowflakeFamiliarity with automated deployment, AWS infrastructure, Docker or similar containersFlexible work from home options available.
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Onsite Hybrid role - 3 days a weekWe are seeking a highly motivated and talented Senior Data Scientist to join our team of experts in developing and maintaining recommendation and personalization algorithms for Disney Streaming's suite of streaming video apps. As a member of our team, you will play a pivotal role in shaping the future of our streaming services by applying state-of-the-art machine learning methods to meet strategic product personalization goals.Responsibilities:
Algorithm Development and Maintenance:Utilize cutting-edge machine learning techniques to develop and enhance algorithms for personalization, recommendation, and predictive systems.Take ownership of maintaining and optimizing algorithms deployed in production environments.Serve as the point person for explaining methodologies to both technical and non-technical teams, fostering clear communication.Analysis and Algorithm Optimization:Conduct in-depth analysis of user interactions within our apps and user profiles to drive improvements in key personalization metrics.Collaborate with data scientists and engineers to refine algorithms and enhance their performance continually.MVP Development:Innovate and develop machine learning products that can be used for new production features or by downstream production algorithms.Work closely with cross-functional teams to prototype and operationalize personalization solutions.Development Best Practices:Maintain and establish best practices for algorithm development, testing, and deployment, ensuring high-quality code and efficient processes.Collaboration with Product and Business Stakeholders:Identify and define new personalization opportunities by collaborating with product and business stakeholders.Collaborate with other data teams to improve data collection, experimentation, and analysis methods.Required Qualifications:
7+ years of analytical experience5+ years of experience developing machine learning models and performing data analysis with Python and tensor-based model development frameworks (e.g. PyTorch, Tensorflow)5+ years writing production-level, scalable code (e.g. Python, Scala)5+ years of experience developing algorithms for deployment to production systemsIn-depth understanding of modern machine learning (e.g. deep learning methods), models, and their mathematical underpinnings for recommendation enginesIn-depth understanding of the latest in natural language processing techniques and contextualized word embedding modelsExperience deploying and maintaining pipelines (AWS, Docker, Airflow) and in engineering big-data solutions using technologies like Databricks, S3, and SparkFamiliarity with data exploration and data visualization tools like Tableau, Looker, etc.Understanding of statistical concepts (e.g., hypothesis testing, regression analysis)Ability to gauge the complexity of machine learning problems and a willingness to execute simple approaches for quick, effective solutions as appropriateStrong written and verbal communication skillsAbility to explain how models are used and algorithms behave to both technical and non-technical audiencesAdditional Preferred Qualifications:
MS or PhD in computer science, data science, statistics, math, or related quantitative fieldProduction experience with developing content recommendation algorithms at scaleExperience building and deploying full stack ML pipelines: data extraction, data mining, model training, feature development, testing, and deploymentExperience with graph-based data workflows such as Apache AirflowExperience engineering big-data solutions using technologies like EMR, S3, Spark, DatabricksFamiliar with metadata management, data lineage, and principles of data governanceExperience loading and querying cloud-hosted databases such as SnowflakeFamiliarity with automated deployment, AWS infrastructure, Docker or similar containersFlexible work from home options available.
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