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Mid-level career experience in Data Science, Computer Science, Machine Learning, Applied Mathematics, or equivalent quantitative field. Full stack experience across analytics, data science, machine learning, and data engineering.
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As a Trust and Safety Machine Learning Engineer, you will work to train models which detect harmful behaviors and help ensure user well-being. Have experience with machine learning frameworks like Scikit-Learn, Tensorflow, or Pytorch.
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You will collaborate with front end, back end, data science, infrastructure, and machine learning engineers to collectively improve the state of engineering at Nextdoor. Python/Django, Java, and SQL experience is a plus.
$153,000 - $212,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Experience building and scaling machine learning models in business applications using large amounts of data. Expertise in Python or Java with and the ability to write performant production-quality code, familiarity with SQL, knowledge of Spark and cloud data environments (e.g. AWS, Databricks.
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Deeply understand the data and customer and business problems, in order to more closely align machine-learning model objectives and develop the best features and models to predict them.
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Research fraud and user behavior to contribute to machine learning models, rules and other detection systems in partnership with our Fraud Data Science team. Understand our products, systems and tools; investigate behavioral patterns through data analysis using SQL and other data scripting and visualization tools.
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The company applies proprietary machine-learning algorithms and data processing resources to measure travel patterns of vehicles, bicycles and pedestrians that enable complex transportation problem solving using analytics available on SaaS platform, StreetLight InSight.
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Lead Machine Learning Engineer. Experience working with cloud-based data warehouses like Snowflake, Redshift, or BigQuery. Experience with data transformation tooling (dbt is preferred), data pipeline services like Stitch and Fivetran, and orchestration tools like Airflow.
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Completed a Bachelor’s and/or Master’s degree related to Computer Science, Statistics or related major studying AI (artificial intelligence), ML (machine learning), NLP (natural language processing), Data Science or Mathematics.
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This is an open-ended entry-level role with mentorship, and diverse opportunities to work on all areas of our product: databases, distributed systems, infrastructure and tooling, data analysis, machine learning, frontend and backend web development, APIs, data mining, data modeling, and more.
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Expertise in statistical modeling, machine learning algorithms, and data mining techniques, with proficiency in programming languages such as Python, R, or SQL. As the Principal Data Scientist for Enterprise Data Science at Gap Inc., you will play a pivotal role in leveraging advanced analytics and machine learning techniques to drive growth, optimize customer experiences, and enhance operational excellence across all Gap Inc. brands.
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Tooling for Machine Learning: data management, model training, validation and deployment (C. Working understanding of Python, Git, SQL, and Terraform. Contribute to a culture of learning, collaboration, and continuous improvement within the team.
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Apply machine learning, causal inference, or advanced analytics on large datasets to: i) measure results and outcomes, ii) identify causal impact and attribution, iii) predict the future performance of users or products, to drive business success.
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Looking for candidate with experience in Data Science, Machine Learning and Marketing Analytics domain experience. 8+ years of Data Science / Machine Learning experience.
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Responsible for the development, enhancement, and production of various predictive and Machine Learning driven models to generate behavioral shopper insights, target audiences, and optimized customer journeys.
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