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Extracts and analyzes complex information from large structured and unstructured datasets using data mining and data modeling, NLP, and Machine Learning (ML). Generates analytical and data insights to drive business actions using SQL, Qlik/Tableau, Python, and R. Creates complex, automated analytics solutions using Text Mining and Natural Language Processing (NLP) tools.
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Continuously monitor and improve the performance of machine learning models through data analysis and testing. Senior Machine Learning Engineer page is loaded.
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Minimum 2 years of experience with large-scale data processing platforms such as Spark, EMR, and/or HPC computing experience with e.g. Apache Aurora, Slurm. Assist and advocate for bringing new technologies for data management, governance, and usage.
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Working alongside our generalist consultants, Bain's Advanced Analytics Group (AAG) helps clients across industries solve their biggest problems using our expertise in data science, customer insights, statistics, machine learning, data management, supply chain analytics and data engineering.
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Ideal candidates will possess: Familiarity with analyzing oncology clinical dataFamiliarity with DBT workflowsFamiliarity with creating and maintaining BI dashboards; Looker experience nice to haveFamiliarity with machine learning techniques, with an understanding of the strengths and limitations of various approachesProficiency in navigating large, complex problems within a fast-paced environment.
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The team leverages its experience in the fields of signal processing, computer vision, computational linguistics, machine learning, artificial intelligence, communication systems, and other areas of electrical engineering and computer science to create impactful solutions.
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In this capacity, this leader oversees a team of computational scientists and develops and guides the implementation of cutting-edge computational approaches, including Artificial Intelligence (AI) and Machine Learning (ML), to target identification, pathway analysis, biomarker discovery, and the design and optimization of both small and large molecules.
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With a bridging seat on the leadership team of DSI, the Head of Computational Science & Data Strategy, Research, ensures a seamless connection with the data infrastructure and governance responsibilities of DSI and its responsibility for enterprise data solutions in partnership with Takeda’s corporate Data & Technology function.
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We want Data Science/Machine learning/Data Analyst and Java Full stack candidates. Currently, We are looking for entry-level software programmers, Java full-stack developers, Python/Java developers, Data analysts/ Data Scientists, and Machine Learning engineers for full-time positions with clients.
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Reporting to the Senior Director / Head of IT, you will work alongside Data Science, Research, Clinical, and TechOps teams to spearhead the architecture design and deployment of data products, supporting the goals of Data Science, Bioinformatics, and Machine Learning.
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Ensure a Data Steward is assigned, and that Data Governance and Data Privacy guidelines are completed by the team when data is involved. We provide investment servicing, data & analytics, investment research & trading and investment management to institutional clients.
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Analytical Skill, Analytical Skill, Analytical Thinking, Chemical Biology, Chemistry, Clinical Trials, Collaboration, Communication Skills, Curiosity, Data, Data Analysis, Design Of Experiments, Detail-Oriented, Drug Development, Drug Discovery, Ethics, Gene Therapy, Immunology, Inventory Management, Laboratory, Lifesciences, Machine Learning (Ml), Management, Medical Research, Molecular Biology {+ 10 more.
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This entails designing and implementing a sophisticated data governance framework spanning across capabilities and tools such as data quality checks, defining/tracking KPI’s, data lineage and data structure and organization (e.g. organized data hierarchies, well-maintained data dictionary and report catalogue, as well as data and report certification.
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Any specific experience with data management best practices, data governance, data quality controls, regional or regulatory reporting requirements is preferable. The person will work directly with stakeholders across - ESG Investments, ESG Product Strategy, ESG Data and Operations, Client, Product and Regulatory Reporting, and Enterprise Risk Management to understand their data and reporting requirements and to translate requirements into functional specifications for technology partners building/ enhancing IT solutions for ESG reporting.
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Experience with data visualization tools (e.g., Spotfire) and advanced analytics techniques (e.g., machine learning) is required. You will also work with scientists and with experts in data management, lab automation, molecular design, and machine learning in the Global Biologics organization to build and continuously improve data infrastructure.
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machine learning data governance processing database architect jobs Title: data engineer in Boston, MA
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