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In our Data science track we prepare you to get job as one of the following: Python developer, a data analyst, data visualization developer, a statistician, a machine learning engineer or a data scientist.
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Demonstrated expertise in machine learning, deep learning, and NLP, with a strong portfolio in large language models like GPT-3, BERT, and RAG.Advanced proficiency in Python, with hands-on experience in ML libraries and frameworks such as TensorFlow and PyTorch.
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With PySpark, Python, SQL, Excel, and data visualization tools (Tableau, Power BI, etc.) of machine/deep learning techniques and algorithms (XGBoost, random forests, logistic regression, SVM, KNN, k-means clustering, PCA, neural network, deep reinforcement learning, etc.
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Proficiency with PySpark, Python, SQL, Excel, and data visualization tools (Tableau, Power BI, etc.) Excellent understanding of machine/deep learning techniques and algorithms (XGBoost, random forests, logistic regression, SVM, KNN, k-means clustering, PCA, neural network, deep reinforcement learning, etc.
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Strong experience with machine learning technology, such as: big data stack, Python, R, and visualization techniques. + Advanced degree preferred, with 5+ years of experience in Applied Econometrics, Statistics, Data Mining, Machine Learning, Analytics, Mathematics, Operations Research, Industrial Engineering, or related field preferred.
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You must be familiar with image processing, machine vision, and data engineering, and even better if you are interested in 3D rendering, deep learning, and computer graphics. At a minimum, you should be able to implement and optimize deep learning algorithms developed by others.
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RNN) in a work setting, not just academic projects Hands-on experience in building and deploying machine learning and statistical models using Python, PySpark, Machine Learning libraries, SQL. Experience in computing/programming skills; proficiency in Python, R, and Linux shell script.
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Leadership - Microsoft Azure - AWS - Machine Learning - Data Science - Python R - GCP. Machine Learning Algorithms - Deep Learning - Artificial Neural Networks.
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Our employees bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data.
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Extensive knowledge of machine learning algorithms, including a deep understanding of statistical modeling, and Python development tooling and libraries: Pandas, Numpy, Scikit-learn, Pytest, PySpark,Airflow, MLflow, HuggingFace Transformers, Tensorflow or Pytorch.
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Extensive experience with data manipulation libraries, deep learning, machine learning frameworks and data modelling (e.g., scikit-learn, TensorFlow, PyTorch). Proficiency in programming languages such as Clojure, Scala and Python.
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Python or related language- Experience with neural deep learning methods and machine learningPREFERRED QUALIFICATIONS- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
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2-5+ years of experience in wide range of statistical and machine-learning techniques (e.g. time series analysis, NLP, deep learning and etc.) Conduct research on cutting edge technologies in AI/BI/ML/NLP, alternative data, FinTech, high performance computing (e.g. GPU, quantum computing) to discover the potential opportunities to the business applications.
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Whether it's holding a PhD-level deep dive into understanding fairness and underlying bias in machine learning models, debating the merits of a Scandinavian design philosophy in our UI/UX, or writing responses for Medicare rules to influence U.S. health policy, we prioritize sharing our findings across the team and helping each other be successful.
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Deep understanding of predictive modeling, machine-learning, clustering and classification techniques, and algorithms. Fluency in a programming language (Python, SQL, SOLR) Master's degree or equivalent experience in Computer Science, Data Science, and Bioinformatics field.
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