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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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Hands-on experience with data analytics and classical machine learning tools(like pandas, NumPy, scikit-learn)and deep learning frameworks(like Tensorflow, Lang Chain, Pytorch, Flask, Fast API.
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Candidate will be given the opportunity to learn and make use of sophisticated tools (SQL, Alteryx, Informatica, SAS, Tableau, SSRS, DataRobot etc) and technologies (Big data like Hadoop, Python/R Programming, AI/Data Science,) to provide customized automated solutions across multiple business segments.
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In supporting rule analysis, Teammate should be able to Independently perform sophisticated data analytics that fit to the fraud problem being observed (ranging from classical econometrics to machine learning, neural networks, and natural language processing) in a variety of environments using structured and unstructured data.
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Proficient with the core concepts of at least one programming language such as Python, R, and SQL and adept with machine learning frameworks such as TensorFlow and PySpark.
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Our client is currently seeking an experienced Data Engineer – Big Data individual for their Midtown office in Atlanta, GA. The successful candidate must have Big Data engineering experience and must demonstrate an affinity for working with others to create successful solutions.
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Certified Analytics Professional (CAP), Data Science Council of America (DASCA), Principal Data Scientist (PDS), SAS Big Data Professional, Microsoft Certified Azure Data Scientist Associate, or equivalents.
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Our work includes novel areas including machine learning/ AI, data visualization, and cloud technology. + A minimum of three (3) years of experience using R programming language (Python is a plus.
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Experience in Natural Language Processing, Machine Learning Ops and data pipelines. Lead Machine Learning Engineer. Serve as a subject matter expert in machine learning and fintech domains.
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Advanced proficiency in Qualtrics/Clarabridge, SPSS, SQL, R, Python, Tableau and Power BI. Qualtrics Customer XM and XM Discover Advanced Proficiency, SQL, R, Python, SPSS, PowerBI, Tableau.
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The ideal candidate will be skilled in statistical analysis, machine learning, and leveraging Azure technologies in big data to drive significant business impact. Metas Solutions has an "immediate" opening for an experienced Data Scientist/Machine Learning Engineer to work Remotely.
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Azure Databricks Platform Architect certification, Databricks Accredited Lakehouse Fundamentals certification, or similar certificationsWorking experience with Tableau, SAS Viya, R, and/or python.
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Prior experience with Intex, Moody’s Analytics, Crystal Ball, R, Python, and other industry software, preferred. Experience valuing structured products such as collateralized debt obligations including building cash flow waterfalls and experience with the use of industry data bases.
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Knowledge of R/Python/SQL. Excellent communication and interpersonal skills, with the ability to effectively train and support users at all levels of the organization. Experience connecting Tableau to various data sources, including relational databases (e.g., SQL Server, MySQL), cloud platforms (e.g., AWS, Google Cloud), and flat files (e.g., CSV, Excel), to extract and transform data for analysis.
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You will have indepth knowledge and experience in; cloud data lake house; Databricks (preferred) or Snowflake; cloud-native solutions knowledge; SQL or Python; modern DevOps approach; have written data code AND also the CI/CD pipelines.
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