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The software engineer will work in a general office environment alongside MGH/Harvard/MIT faculty, postdoctoral fellows, data analysts, research technicians, and students. The software engineer will work closely with researchers from a wide range of backgrounds (e.g., engineering, neuroscience, computer science)to build, improve, test, support, and document image analysis software.
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Expert knowledge of financial data platforms such as Bloomberg, Capital IQ, Refinitiv, WRDS, FactSet, and/or other business information platforms. 5+ years of experience providing research and/or data support in business, finance, economics, and/or other social science research environments required.
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Job Schedulers – Airflow, Oozie or other ETL Scheduler Data Analytics – AWS Cloud Native Services Big data architecture – Python, Scala, Hadoop Bigdata, Hive, Pyspark etc. Lead development of digital architecture blueprint, technical roadmaps, technology frameworks for software, data, integrations and infrastructure solutions Lead proposals for Digital Transformation and Cloud Computing and High-Performance Computing RFPs Provide thought leadership on Digital architecture roadmap to Business and IT leaders and enterprise architecture teams.
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Take ownership of new feature and automation development, write unit tests, self tests, and QA software, continuously delivering high quality engineering results. We prohibit discrimination based on race, religion, color, national origin, sex, pregnancy, reproductive health decisions or related medical conditions, sexual orientation, gender identity, gender expression, age, veteran status, disability, genetic information, or other characteristics protected by applicable local, state or federal laws.
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Driving Results: Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using Python and/or Node.js, SQL (using dbt for transformation), commercial SaaS and OSS offerings, and AWS ‘big data’ technologies.
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Position requires a Bachelor’s degree in Finance, Computer Science, Engineering Management, or other related field plus five (5) years of experience in the job offered or five (5) years of experience as a Senior Application Support Engineer, Data Analyst, or a related occupation.
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At 1910 Genetics, we put computation at the heart of drug discovery, blending expertise in computational chemistry, structural biology, pharmacology, genetics, data science, and software engineering to develop drugs for previously undruggable targets.
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The Talend ETL Developer is a key member of CHIA’s software development organization and our Data Operations and Technology team reporting to the Associate Director of Master Data Management and ETL Design.
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Develop and execute strategies that maximize the value of data science applications (e.g. in AI/ML, Computational Chemistry, and Biology). Moreover, this embedding with DSI nurtures fertile Research and Development collaborations that leverage DSI’s excellence in quantitative pharmacology, biostatistics, and big data.
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This involves the development of a control system architecture, selecting the components to be used, detailing schematic diagrams and system documentation, programming controllers (PLC, DCS, RTU), programming the process visualization (HMI/SCADA), developing databases for archiving/displaying historical system data and implementing/commissioning the control system at the client’s facility.
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We have expertise in water supply planning, groundwater and surface water modeling, water quality, stormwater/BMPs, collection system modeling and design support, hydraulics, hydrodynamic modeling, dam safety and emergency action planning, floodplain mapping, water distribution modeling, coastal erosion, sustainability and climate resiliency planning, data analytics, dashboards, watershed management, ocean outfalls, wave modeling, effluent recharge planning, and permitting support.
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5+ years of experience in data analysis or data science, with 3+ years focusing on machine learning problems, ideally in a relevant space (KYC, sanctions detection, anti-fraud detection, treasury management, crypto/blockchain data science.
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The VP, Engineering will lead scaling the global data and software engineering teams in managing the foundational enterprise data platform and creating tools and frameworks that enhance data collection and processing, analytics and artificial intelligence, data dissemination, and governance.
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Bachelor’s degree (or foreign education equivalent) in Applied Computer Science, Computer Science, Engineering, Information Technology, Information Systems, Information Management, or a closely related field and three (3) years of experience as a Senior IT Data Analyst (or full stack engineering or closely related occupation) performing data analysis and modeling using SQL, PL/SQL, and Python in a financial and brokerage services domain.
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Bachelor s degree (or foreign education equivalent) in Computer Science, Engineering, Information Technology, Information Systems, Information Management, Business Administration, or a closely related field and six (6) years of experience as a Director, Data Analytics and Insights (or closely related occupation) performing data analysis using Snowflake, SAS, SQL for data querying, Python, and Alteryx.
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big data science information software engineer jobs Company: Leading Path Consulting in Boston, MA
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