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Responsibilities:Lead the growth of Data and Analytics practice for Financial Services and InsuranceProvide technical expertise and guidance on the selection, and hands-on implementation, and optimization of big data platforms, tools, and technologies across multiple cloud environments (e.g., AWS, Azure, GCP, Snowflake, etc.
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Experience with cloud computing platforms (, AWS, Azure, GCP) and cloud native computingProficiency in programming languages like Python, Java, Scala, C#, SQLExpertise in big data technologies such as Hadoop, Spark, Kafka, and NoSQL databasesKnowledge of data modeling, ETL processes, and data warehousing conceptsExceptional problem-solving abilities and teamwork skills.
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Hands on experience with programming for extract transform operations and data analysis using languages such as, but not limited to R, Python, SQL, and Excel VBA. Experience in developing data visualization and business intelligence solutions using tools such as, but not limited to, Shiny, Tableau, PowerBI, and front-end technologies and languages.
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Onboard datasets, explore data, and automate tasks using a modern Python data stack. Experience with financial datasets (e.g. Refinitiv, S&P, Bloomberg) is a big plus. Hudson River Trading (HRT) is looking for a Data Production Engineer to join our Data team.
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Proficiency with Excel / VBA and R / Python. Bachelor's degree in Financial Engineering / Quantitative Finance, Math, Statistics, Data Science, Engineering, Economics, or other relevant program.
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Fluency in the languages of data manipulation (e.g., SQL) and statistical analysis (e.g., R or Python/NumPy), with ability to code (e.g., PHP) a plus, Java, Ruby, Clojure, Matlab, Pig or SQL.
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You have working knowledge of analytic technologies (e.g. Alteryx, SAS, SQL, R, Python, Power BI, Tableau, Adobe Analytics, etc.) We are looking for a Data Analytics professional to be a creative and collaborative team member, embedded within a Data Intelligence team focused on client reporting and analytics, KPI development, campaign measurement, research and insights with a focus on delivering reports, dashboards, ad hoc analyses and strategic insights across a wide array of client sectors.
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You must be passionate about data management with a solid background in AWS, Databricks, Python, Trino/Starburst, Databases and SQL.Design, develop, monitor, and maintain data pipelines in an AWS Gov Cloud ecosystem with AWS, Databricks, Delta Lake and Trino as the underlying platforms.
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Experience working on Big Data Technologies. Hadoop Admin Ops / SRE role supporting Platforms built around Big Data Technologies (Hadoop, Spark, Kafka, Impala, Hbase, Docker-Container, Ansible and many more.
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Experience in Data science and Machine learning using Python, R, Java, C#, Spark, AutoML, TensorFlow, Amazon AML, Microsoft machine learning studio, PyTorch, IBM Watson and any graph DB.
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Hands-on development experience with Snowflake features such as Snow SQL; Snow Pipe; Python; Tasks; Streams; Time travel; Zero Copy Cloning; Optimizer; Metadata Manager; data sharing; and stored procedures.
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Hands on experience in data engineering desired with extensive knowledge of SQL and PySpark, on Databricks Platform. Ability to design cloud and on premise data solutions and provide guidance across storage, big data platform services, Big Data ecosystem, vendor SaaS integrations, RDBMS and NoSQL databases is a plus.
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Experience building loan-level credit/prepayment models from data preparation, data analysis, and model estimation through deployment into productionExperience with generalized regression models as well as machine learning frameworksVery strong programming and software design skills (Python, C.
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Strong foundational understanding of Big Data ecosystems to make trade-off decisions while developing end to end solutions on Cloud/On-Prem/Hybrid Data tech stackExperience balancing new product development with maintaining day-to-day data reporting operations in a very large scale enterprise set upExperience applying both qualitative analysis and quantitative analysis techniques and familiarity with common data science models and approaches to problem-solving.
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Strong experience with machine learning technology, such as: big data stack, Python, R, and visualization techniques. + Build and lead a team of data scientists, organizing analytical processes and workflows, and mentoring/developing the managers what work on your team as well as junior team members.
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hands on big data r python jobs in New York, Norwood, Massachusetts
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