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Using tools such as SQL, DataBricks, Talend, Python, Microsoft Power Platform and Azure Data Factory. Cloud Computing – Use the full range of Microsoft Azure Services with exposure to machine learning.
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You should be comfortable writing SQL queries and have basic familiarity with another programming language. You should be familiar with Python and be able to demonstrate the ability to write scripts, test and deploy code.
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Expertise in Python with and the ability to write performant production-quality code, familiarity with SQL, knowledge of Spark and cloud data environments (e.g. Azure, Databricks). The Information Technology team has the mission of becoming a true business partner and we are searching for a Senior Machine Learning Engineer to help execute on this mission.
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Apply machine learning, econometrics/statistics, predictive modeling, return-on-investment analysis, simulation, and data visualization methods to support the development of health policy.
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Knowledge of predictive modeling, statistical sampling, optimization, machine learning and artificial intelligence techniques. Strong Programming skills e.g. R, Python, SAS, SQL, R or other languages.
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Experience developing and applying statistical or machine learning methods in a corporate environment through applications such as R, python, SAS, SPSS, S, S-PLUS, or Stata. Minimum of 4+ years of experience using data manipulation tools such as SAS, SQL, R, or Python, Business Objects, or other tools to query large databases and manipulate large data files.
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Experience using one or more relevant data science programming languages such as, R, Python, SQL, MATLAB; the use of an integrated development environment (IDE) such as, RStudio. Experience in the use of relevant data science programming languages such as, R, Python, SQL, MATLAB, and experience using an integrated development environment (IDE) such as, RStudio.
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Preference will be given to candidates who have demonstrated experience developing or implementing informatic and/or advanced data analytics (e.g., machine learning) solutions and those with proficiency in programming languages commonly used in data science (e.g., R, python, SQL.
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Advanced proficiency in programming languages such as (R / Python / Java / C#), SQL. Advanced proficiency with machine learning frameworks such as Keras, PyTorch, or Tensorflow and libraries such as numpy, scikit-learn, scipy and statsmodel.
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Continuous Learning – stay up-to-date with emerging technologies, changes in the banking industry, and regulatory developments. We are working on challenging projects, migrating ETL jobs from Talend to DataBricks, building workflow automation solutions using Microsoft Power Platform, data flows with Azure data lake storage and DevOps environment set up.
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You have knowledge and experience in digital signal processing, statistical process control and machine learning. such as Python, SQL, JAVA, C , C, MATLAB. As a senior consultant in the Data Driven Transformation Team of Capgemini Invent you will help clients in the manufacturing sectors transform and improve their operations by leveraging insights from underlying business, process and machine data.
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Experience with disciplines such as: predictive modeling techniques (ex: random forests), scripting languages (ex: python), coding best practices (ex: version control), SQL (ex: Oracle, PL/SQL), and big data environments (ex: AWS, GCP, Azure, Hadoop.
$106,960 - $160,440 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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As a Senior 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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Required Skills & Experience 3+ years of Data Engineering experience Jav SQL NoSQL Database experience Python AWS Spark, Kafka, or Flink Desired Skills & Experience Masters degree or higher in Computer Science or related field.
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Experience leveraging complex data to drive business decisions, hands on experience in data science methodologies (predictive analytics, machine learning, patient level data triggers) using R, Pytong, Databricks and deep knowledge of Qlik, PowerBI, Tableau for visualization.
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