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Our products are trusted by leading companies including PayPal, Visa, FTX, Uniswap, Anchorage, and federal agencies such as the FBI and IRS. Every day, we tackle challenges in data engineering, data science, and threat intelligence to advance our mission to build a safer financial system for billions of people.
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Job Description Data Engineer (SS&C Technologies, Inc.; San Francisco, CA): The Data Engineer will: Create a leading cloud platform with the latest big data, cloud native and machine learning technologies.
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Experience with data visualization tools, knowledge of data engineering, data modeling, and big data technologies. As the leader for Product Data Science, you will establish the roadmap for your team and implement projects in data science, artificial intelligence, machine learning, and product insights.
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We do this by providing businesses with access to world class, on-demand data science talent that helps them solve real business problems. You love machine learning and data science, and are always up to speed with the latest developments in the space.
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New York City (Hybrid On-Site): $161,900 - $184,800 for Data Science PhD San Francisco, California (Hybrid On-site): $171,500 - $195,800 for Data Science PhD Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.
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Softrams is a Maryland and Virginia-based small business information technology, consulting, and solutions provider specializing in emerging technologies for UX/UI, mobile apps, DevOps, big data analytics, data science, and cyber security.
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Candidates should be familiar with some of the following: subsurface imaging with passive seismic data, geomechanics, earthquake characterization, seismicity forecasting, seismic wave physics, big data processing, machine-learning-based processing, distributed fiber optic sensing, seismic sensors and deployment, hydraulic fracturing, and/or geothermal exploration.
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You can help us build an InsurTech company that uses the latest technology, data science, and behavior modification methods to save lives by preventing car collisions before they happen.
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Experience building large scale data sets in AWS, Hadoop or similar big data environments. Using your affinity for synthesizing and visualizing data, domain expertise, data mining and communication skills, you’ll ensure we’re building the best product for our current and future Pinners.
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As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
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Experience with designing and maintaining data warehouses and/or data lakes with big data technologies such as Spark/Databricks, or distributed databases, like Redshift and Snowflake, and experience with housing,accessing, and transforming data in a variety of relational databases.
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The Data, Insights, Science and Optimization, Consumer Product and Tech (DISCO CPT) team is looking for a Principal Product Manager -Technical to join a team of Data Scientists, Analytics Leads, Business Intelligence Engineers and Data Engineers who analyze big data, provide analytics and insights as well as build models and algorithms that power product for personalized experiences.
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Data Science problems are everywhere, but the talent is not. Obviously AI is backed by some of the top venture capital firms in the US, and you’ll be on the ground floor of a fast-growing company with a big mission.
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We are seeking a Senior Product Manager-Technical (PM-T) to join the Data Insights Science and Optimization (DISCO) team within Amazon Music. You have a deep understanding and natural curiosity for data science and data products.
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Exposure to big data platforms, such as Snowflake, Redshift, Azure, Matillion, Alteryx. Good familiarity with the principles of data science and data engineering. Bachelor’s Degree in a quantitative field (Statistics, Data Science, Finance, Math, CS, or related) with 8+ years of relevant experience in customer behavior analytics, or Advanced Degree in a quantitative field with 5+ years of relevant experience.
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