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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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Alternatively, the employer will accept a Master’s degree in Finance, Computer Science, Engineering Management, or other related field plus three (3) years of experience in the job offered or three (3) years as a Senior Application Support Engineer, Data Analyst, or a related occupation.
$169,104 - $199,104 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Strong knowledge, experience, and fluency in a wide variety of tools including Python with data science and machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch), Spark, SQL; familiarity with Alteryx and Tableau preferred.
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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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Expertise in all aspects of biomarker science i.e. genetics, genomics, molecular and cellular, digital devices, imaging and data sciences; cellular kinetics. Collaborate with Research teams to bridge non-clinical data into clinical development, and establish credible, clinically based biomarker, and cellular kinetics plans, as well as clinical data review.
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Prior experience in data science/AI/BI tools. Focus on software development life cycle, you will collaborate with our Head of Technology Strategy, Head of Data, Solution Architects, Data Analysts, Data Team, and Portfolio Delivery function Leads to understand customer and technical needs to design and implement the Global Investment data platform, including Persistence, Integration and Services layers of the business solutions in compliance with architecture principles and standards followed by MMC technology.
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Job Title: Data Architect with AWS Database / Data Warehouse / Data Platforms (Kinesis, Glue, Redshift, S3) – Not looking for Azure or GCP exp. Minimum 4 years of experience with ETL/ELT design and development using tools like Talend, Informatica, AWS Glue, Oracle Data Integrator (ODI) or equivalent.
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Preferred Area of Experience: Microsoft 365, Power Platform (PowerApps, Power Automate, Power Pages, Dataverse, Power Virtual Agents/Microsoft CoPilot), Fabric (Power Bi, OneLake, Factory, Synapse Data Warehouse, Synapse Data Engineering, Synapse Real-Time Analytics), SharePoint, Windows Server, Azure, DevOps, CI/CD Pipelines.
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As part of the Biomarker Science & Technologies (BST) group at Takeda, you will report to the Head of Sample and Data Operations, Director and you will will w ork to advance the mission of BST and its contributions to the clinical program lifecycle.
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Data science and data mining background with special emphasis on MS SQL, R, Python. Participate in data delivery for clients of custom data cuts of IHS Markit TRANSEARCH database.
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Experience using one or more relevant data science programming languages such as, R, Python, SQL, MATLAB; the use of an integrated development environment (IDE) such as, RStudio. Experience in the use of relevant data science programming languages such as, R, Python, SQL, MATLAB, and experience using an integrated development environment (IDE) such as, RStudio.
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Minimum 5 years of experience with ETL/ELT design and development using tools like IICS, AWS Glue, Talend, Databricks, Oracle Data Integrator (ODI) or equivalent. 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.
$143,500 - $179,960 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Proficiency in statistical programming languages (e.g., SAS, R) and clinical data management systems (e.g., Medidata Rave, Oracle Clinical) is essential. The Senior Vice President (SVP), Head of Data Analytics leads a multidisciplinary team responsible for biostatistics, statistical programming, and data management.
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Familiarity with the modern data science tools such as Pandas, Scikit-Learn, XGBoost, TensorFlow/Keras, MLFlow, Jupyter Notebooks. Use your understanding of Security Data Science, Graph Theory & Machine Learning applications to wrangle our unique cybersecurity data and create analyses and tools that point to the most significant business, governance, and risk management impacts.
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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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data science jobs Title: data Company: Cambridge Sports Analytics in Boston, MA
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