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Provide statistical expertise in clinical trials and collaborate with Clinical Research and Medical Writing groups on clinical trial protocols, case report forms, statistical analysis plans and other study related documents.
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Knowledge of basic statistical analysis and software for flow cytometry. Our client near Upper Manhattan is seeking a Flow Cytometry Medical Technologist to join their Laboratory Team. Must have New York State Clinical Laboratory Technologist License.
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Work closely with trading desks to develop statistical arbitrage strategies and other quantitative trading models. Quantitative Research (QR) is an expert quantitative modeling group in J.P. Morgan, as well as an industry leader in financial engineering, data analytics, statistical modeling and portfolio management.
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Title: Sr Statistical ProgrammerLocation: Boston, MA or RemoteThe role of the Statistical Programmer is to perform statistical programming activities for all assigned clinical studies sponsored by Galderma.
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Familiarity with cloud platforms like Azure (Virtual Machines, Object storage)• Basic understanding of networking, security, and system administration concepts• Detail oriented, with excellent communication, and interpersonal skills• Strong analytical skills coupled with technical curiosityData Science InternAs a Data Science Intern on the Data Platform National Team, you will under close supervision, develop quantitative models and statistical analyses for insurance risk modeling.
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Experience may be gained concurrently and must include one (1) year in each of the following:-Building statistical models and machine learning models using large datasets from multiple resources-Working with Customer, Content, or Product data modeling and extraction-Using database technologies such as SQL or ETL-Applying specialized modelling software including Python, R, SAS, MATLAB, or Stata.
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Must have 3 years of recent experience in financial engineering or statistical software package such as a Matlab, Stata, Bloomberg, or MS Excel/VBA. Analyze and develop models to value a variety of financial instruments, using option pricing theory, fixed income and structured finance models, Monte Carlo simulation, statistical analysis, and other techniques from the financial engineering literature.
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Lead and oversee the design and execution of advanced data science projects, including predictive modeling, machine learning, deep learning, and statistical analysis. The ideal candidate will have a robust background in data science, advanced modeling techniques, deep learning, and Generative AI. Proficiency in Python, SQL, and experience with Nielsen or IRI data is essential.
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Statistical analysis, DNA sequencing, genomics, biochemistry, design of DNA assays, and CRISPR. Statistical analysis, DNA sequencing, genomics, biochemistry, design of DNA assays, and CRISPR. In this position, the candidate will gain experience working with a cross-functional wet-lab/dry-lab team, and they will support our NGS and CRISPR product development efforts.
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Strong background in machine learning, deep learning, and statistical modeling with hands-on experience in developing and deploying ML solutions. Our team is made up of experienced engineers from companies like Two Sigma, Palantir and Google, dedicated to driving the next generation of decentralized AI use-cases on the blockchain.
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Performing statistical analysis, scripting, and predictive modeling using Python or R. Proven commercial experience designing, executing, and analyzing statistical tests (i.e., A/B) Proficient in building customized dashboards using BI tools (i.e., Looker, Power BI, Qlik, Tableau.
$180,000 - $210,000 a yearFull-timeExpandApply NowActive JobUpdated 14 days ago - UpvoteDownvoteShare Job
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Fluency with a statistical programming language (Python preferred) Asset/Investment Modeling, Asset Class Expertise, Capital Markets, Client Relationship Management, Continuous Improvement Mindset, Data-Based Decision Making, Equity Investments, Executive Presence, Financial Risk Management, Investment Accounting, Investment Management, Investment Research/Analysis, Portfolio Management.
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Explore and experiment with new ways of leveraging data and statistical methods to enhance the quality of the demand forecast and generate valuable business insights within and beyond the Demand and Supply Planning (DSP) function.
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Apply statistical and causal modeling techniques to solve various climate implications research questions, using programmatic statistical software packages such as R, Python, and SQL, Postgres, PostGIS, and others.
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Lead and guide the development and implementation of data mining and statistical modeling techniques to analyze complex real-world evidence (RWE) datasets. Strong knowledge of data mining, statistical modeling, and machine learning algorithms.
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psychometrics statistical jobs in New York, NY
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