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Proficient in scripting languages (e.g., Python) and/or mathematical/statistical software (e.g., R), and other advanced analytical tools (e.g., Sagemaker, Tableau, PowerBI, Quicksight, Visier, Alteryx.
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Stay at the forefront of latest trends in machine learning, statistical test design, media mix modeling, artificial intelligence, and other data science fields. Master's degree in Computer Science, Engineering, Business Administration, or related area and 8 years' experience as a product manager, ideally working on consumer-facing, large-scale, highly complex B2B/C products, Supervisory experience, We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly.
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Perform statistical and economic research using financial or alternative data to develop new return predictive signals. Experience in quantitative research at an asset manager or hedge fund preferred.
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As an Associate in our Risk Analytics and Modeling team, you’ll have the opportunity to apply your quantitative, modeling and analytical skills in a real world environment to develop or validate statistical, financial engineering, and AI/machine learning models in the areas of credit risk, market risk, assets and liabilities management, fraud detection, anti money laundering and other functional modeling and analytics area.
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Experience and proficiency with Python, machine learning tools (e.g., scikit-learn, spacy, nltk), deep learning (e.g. huggingface, pytorch, tensorflow), statistical packages (e.g., Scipy), SQL/relational databases (e.g., Oracle) and NoSQL databases (e.g., MongoDB, graph database), distributed machine learning (spark), Linux and shell scripting.
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Demonstrated ability in various analytical techniques: comparative ROI, cost-benefit analysis, valuation, statistical models, and cost accounting. Quick learner: Knowledge of Anaplan, JD Edwards, or other financial systems is a plus.
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The Software Engineering Senior Associate, Valuation & Capital Market Analysis – Complex Financial Instruments will be a member of the Data Science team that builds Python based models and related infrastructure to speed up the development and deployment of machine language (ML), statistical and mathematical models at scale and bring game-changing impact to our client’s decisioning.
$90,000 - $115,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Req’d skills: statistical & coding tools (SAS, R, Python); machine learning model dev (gradient boosting machines, support vector machines, decision trees, regression tech); structured databases; analysis & manipulation of complex and high-volume credit data from varying sources; T-SQL; AWS redshift; Tableau.
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Bachelor's degree with quantitative underpinning (i.e., Mathematics, Statistics, Finance, Economics, or, Engineering) and 5+ years of Consumer Lending statistical modeling/analytics experience; or in lieu of a degree 9+ years' experience in Risk, Credit, Finance, Accounting, Consumer Lending, and/or other relevant professional experience.
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Experience with AWS Cloud suite, Snowflake, Oracle HCM, Service Now, Saba a plus. 5+ years of client-facing People Analytics, Workforce Strategy, Business Intelligence, or Human Capital Consulting experience, working in/with complex organizations, or combination of education and experience.
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GSS models are applied to market-neutral long/short portfolio in AQR hedge funds as well as to long-only, relaxed-constraint and low volatility portfolios for institutional equity mandates and mutual funds.
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Data Analytics experience and skills in data visualization, presentation, statistical programming, critical thinking, and machine learning would be a nice plus. Current certifications in the areas of JavaScript, Cisco CCNA, and Cloud Computing like Google Cloud, Microsoft Azure, Amazon AWS, or CompTIA Cloud+ are a plus.
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Understands mathematical and statistical concepts in addition to transactional actuarial pricing theory. Liaise with Underwriting, Claims, Reserving, and the Managing Actuary to ensure that pricing reflects all relevant information.
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Proficiency in quantitative analysis techniques, statistical modeling, and programming languages such as Python, R, or MATLAB. Identify and quantify various sources of risk, such as credit risk, interest rate risk, and liquidity risk, and develop strategies to mitigate these risks.
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In-depth knowledge of statistical modeling concepts including ability to understand, evaluate, and design code written in R, Python, and/or SAS as well as working knowledge of commonly used statistical programs like Stata and statistical modeling techniques and add-ins in excel.
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statistical job in Port Chester, NY
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