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Experience in ETL/ELT, data acquisition and ingestion, data integration, and CDC tools such as Informatica, Talend, CloverDX, DBT, Qlik Replicate or others. Familiarity with Data Lake, Snowflake, Redshift, Hadoop, ensuring optimal use of analytical data stores.
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Regularly conduct, analyze and present reporting on rental business metrics to provide overall visibility to the organization about data related to rental equipment, looking for trends, areas of opportunity, and process improvement opportunities.
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Evaluate and apply theoretically rigorous results to the development and evaluation of algorithms supporting engineering, signal processing, and machine learning applications based statistical methods.
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Experience with Big Data and technologies such as Map/Reduce, Hadoop, Pig, HBase, Hive. Build fault-tolerant distributed data processing systems from ground up. You have a rock-solid foundation in Computer Science (data structures, algorithms, software design.
$147,520 - $203,000 a yearFull-timeExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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Proven experience building models from a blank page and owning the entire deep learning stack including data curation, characterization and cleaning, architecture design and model building, distributed large-scale training, and model optimization for inference.
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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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Bachelors degree in Data Science, Economics, Business, Statistics, or related field +1 years of experience using SAP Crystal Reports, Tableau, SQL, Python, R, and SPSS to support business intelligence reporting and analysis.
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Familiarity with machine learning models and algorithms. To be successful as a Data Scientist on the Field Analytics Data Science team you should have a demonstrated background blending large datasets, statistics, creativity, and consulting into actionable outcomes.
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Growth Potential: Developing a strong foundation in data analytics paves the way for career growth into advanced roles such as data scientist, machine learning engineer, or data engineer.
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Be hungry – Stay informed about industry trends and advancements in marketing personalization, digital innovation, and machine learning to guide internal strategies. Track record of not only building Machine Learning personalization models, but translating it to measurable business impact.
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Working knowledge of either machine learning management systems such as Azure ML, machine learning workflow-engines such as MLFlow/Airflow/Metaflow, or data storage, databases, and structure for large data volumes.
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In this role you will have a good understanding and knowledge of cell biology/cell physiology, biochemistry and knowledge of statistics, data science and machine learning concepts.
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Fast-growing AI company is seeking highly-qualified scientists and engineers with experience in ML (Machine Learning), DL (Deep Learning) and Computer Vision to address real-world challenges in the Health Care industry.
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We are seeking for a Data Scientist/ML Engineer with experience in NLP, statistics, and Conversational AI. The ideal candidate is adept at using Statistical Modelling, Machine learning algorithms and Conversational AI. Strong experience using variety of data mining/ Machine Learning methods, using/coding algorithms and running simulations.
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Utilize: Python, PySpark, Statistical Analysis System (SAS), Machine Learning (scikitlearn, SHAP, MLlib), Deep Learning (TensorFlow), MapReduce, Hadoop, Hive, GitHub, Jira. Required: Master’s degree or equivalent in Computer Science, Engineering, Information Technology, Mathematics, Statistics or related (employer will accept a Bachelor's degree plus five (5) years of progressive experience in lieu of a Master’s degree) and one (1) year of experience as a Data Scientist or related.
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