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As a Staff Data Scientist, you will utilize your expertise in data mining, predictive modeling, machine learning, and NLP techniques to drive strategic decisions for WCS. You will be at the forefront of implementing models and strategies using A/B testing or Design of Experiments (DOE), tracking business performance, and providing insightful visualizations to support and continuously improve WCS business strategy.
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Experience in Data Science, Data Mining, Machine Learning, Predictive Modeling best practices. Experience in Data Science, Data Mining, Machine Learning, Predictive Modeling best practices.
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Ideal candidate is pre-ACAS through new FCAS with 4+ years of P&C actuarial, data science, or predictive modeling experience, including Machine Learning using SQL and Python (including pandas.
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Familiarity with machine learning algorithms and data mining techniques. Use predictive modeling to increase and optimize customer experiences, revenue generation, and other business outcomes.
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2 years of experience must include: Python; R; SQL; Hive; Tableau; Statistical modeling: linear and logistic regression; Machine learning techniques: Support Vector Machines and Random Forrest; and Exploratory and advanced data analytics.
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Partner with multi-discipline digital teams (data analysts, data engineers, data scientists, and business product owners) to advance data analytics tools/features (such as predictive/ prescriptive algorithms and machine learning.
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Master’s Degree in related field (e.g., Data Science, Predictive Analytics, Machine Learning, Statistics, Applied Mathematics, Computer Science) Ability to design and implement end-to-end machine learning pipelines for data ingestion, processing, modeling, and deployment.
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Knowledge of data preprocessing, feature engineering, and model evaluation techniques in machine learning projects. Proficiency in Google Cloud Platform (GCP) services relevant to machine learning and AI, such as AI Platform, BigQuery, Dataflow, and Tensorflow.
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Familiarity with Natural Language Processing, Machine Learning, Predictive modeling, Statistical Analysis and Hypothesis testing. Is familiar with disciplines such as Natural Language Processing, Machine Learning, Predictive modeling, Statistical Analysis and Hypothesis testing.
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Bachelor’s Degree in related field (e.g. Data Science, Predictive Analytics, Statistics, Marketing Analytics, Applied Mathematics, IT) Strong understanding of machine learning algorithms, techniques, and frameworks, including deep learning, neural networks, and ensemble methods.
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Agility to collaborate and influence peers and business partners as organization matures across Enterprise Marketing Data & Analytics (e.g., marketing and ad tech. 4 years of experience in managing, and mentoring data science, data engineering, and/or analytics teams in the financial services industry.
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5-8 years of hands-on experience in data science, with a strong focus on machine learning, predictive analytics, and statistical modeling. This role requires strong expertise in Python, PySpark, Databricks, Java and other relevant technologies, along with a deep understanding of statistical analysis, predictive modeling, and data visualization.
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4 years of experience in managing, and mentoring data science, data engineering, and/or analytics teams in a highly regulated environment. 10 years of experience working in data and analytics, including data governance and data innovation across an organization developing strategies, managing major initiatives, and delivering.
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Experience with building and training machine learning models using tools like TensorFlow, Keras, or PyTorch. Understanding of containerization technologies like Docker for packaging machine learning models and deploying them in production.
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Identifies opportunities to use predictive analytics to drive efforts around customer experience and marketing efforts. Comprehensive knowledge of data integrity/privacy practices and applicable risk and compliance management framework.
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machine learning data mining predictive modeling jobs Company: Visa
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