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Senior Machine Learning Engineer (Python, PySpark, SQL) At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow.
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Preferred skills: NLP, Text mining, Tableau, PowerBI, Databricks, Tensorflow. matlab, perl, python, sdet, software engineer. Knowledge of Statistics, SAS, Python, Computer Vision, data visualization tools.
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Utilize programming languages like Java and Python and working within Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services. Experience with PyTorch and or Tensorflow.
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Strong fluency in Python and SQL, experience with Tensorflow, PyTorch, Airflow and data warehouse. Strong experience with Python/R, forecasting methodologies, machine learning and statistics.
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Experience with tools and frameworks such as Python, TensorFlow, PyTorch, or scikit-learn. Experience with tools and frameworks such as Python, TensorFlow, PyTorch, or scikit-learn. Proficiency in data analysis, statistical modeling, and machine learning concepts.
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Experience working with a variety of modeling tools and platforms commonly used in the insurance industry (e.g., SAS, R, Python, TensorFlow). Experience working with a variety of modeling tools and platforms commonly used in the insurance industry (e.g., SAS, R, Python, TensorFlow.
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Strong expertise in machine learning frameworks (e.g., TensorFlow, PyTorch) and programming languages (e.g., Python, R). Strong expertise in machine learning frameworks (e.g., TensorFlow, PyTorch) and programming languages (e.g., Python, R.
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Expertise in machine learning algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and programming languages (e.g., Python, Java). Expertise in machine learning algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and programming languages (e.g., Python, Java.
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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. Understanding of Finance business processes, including FP&A, Strategic Finance, Business Unit Finance, Controllership (Close & Consolidations), Tax, Treasury, Management and External Reporting, and Investor Relations.
$81,000 - $164,000 a yearFull-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Strong understanding of deep learning frameworks, such as TensorFlow, PyTorch, or MXNet. Choose and optimize backend technologies (e.g., Python, Java, Node.js) based on model requirements and system limitations.
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Command of analytics-based scripting tools and libraries such as Python (pandas, numpy, sklearn, tensorflow, etc.) Python, Pandas, Data Science, Machine Learning, Statistical Learning, Applied Mathematics.
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Proficient with Python and SQL. Languages like Go, Rust, Scala, R, and C. Familiarity with popular machine learning frameworks such as TensorFlow, Proficient with Python and SQL. Languages like Go, Rust, Scala, R, and C.
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Preferred skills: NLP, Text mining, Tableau, PowerBI, SAS, Tensorflow. Currently, We are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/ Data Scientists, Machine Learning engineers for full time positions with clients.
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A minimum of 5 years of professional experience, 3 as a Machine Learning Engineer. Experience integrating with BI tools such as Mode, Tableau, Looker, or. As a machine learning engineer, you will get the opportunity to contribute to, optimize, and deploy many exciting models as well as help the team build net-new features into our machine learning platform.
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Proficiency in Python or R and Client frameworks like TensorFlow or PyTorch. Deep expertise in statistical analysis, predictive modeling, and Client algorithms, especially with LLMs and FMs.
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