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Expert knowledge of at least one data science programming language (e.g. Python, R, Julia, etc.) Earned graduate degree (Ph. D. or M.Sc. + 2 years relevant industry experience) in a highly quantitative discipline (e.g., machine learning, statistics, computer science, applied mathematics, theoretical physics, physical chemistry, econometrics, bioinformatics.
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You will develop robust and scalable data pipelines, ML model hosting, and backend services for enterprise line of business applications in Python, VertexAI, Airflow, dbt, Flask, PostgreSQL, BigQuery, Docker, Kubernetes, and more.
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They will use relevant statistical techniques, machine learning models and artificial intelligence algorithms to analyze data, design data models and derive insights to influence actions that maximize business value and effectiveness for the commercial technology segments.
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Work will involve building semantic search engines, LLM fine-tuning, Vector DB applications, and cutting-edge data science work. Understand business problems, making sense of the data landscape & footprint, performing a combination of Gen AI, Advanced NLP, Exploratory analysis.
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Proficiency in programming languages such as R, Python, and SQL, with experience in data analysis and machine learning tools like PyTorch, Pandas, scikit-learn, Tensorflow, or similar.
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Deep Learning Ninja: Proven experience in designing and implementing machine learning solutions utilizing GCP and various algorithms (e.g., TensorFlow, PyTorch). As a Machine Learning Engineer specializing in Google Cloud Platform (GCP), youll lead the charge in developing and deploying cutting-edge solutions that extract valuable insights and drive tangible business outcomes.
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Minimum Experience: 2 years of industry experience in dedicated machine learning or data engineering roles, or equivalent to a Master’s degree with strong emphasis in Machine learning.
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Hands-on experience with analytics and big data technologies within Microsoft Azure, with experiences in tools such as Azure Data Factory, Azure Machine Learning, Azure Cognitive Services, Azure Databricks and Azure Synapse Analytics.
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Experience in statistical programming languages such as SAS, R, Python, etc. They will design, develop, and execute analytic plans using statistical software such as SAS, R, Python, or Stata.
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Continuously improve knowledge and abilities in the areas of software and data engineering, statistical learning, and machine learning. 3+ years Demonstrable experience building statistical models and machine learning models in Python or R.
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Apply statistical, machine learning, and NLP techniques to identify patterns, extract meaningful insights, or develop new tools or solution for the business stakeholders. + Data visualization tools such as Power BI or Qlik Sense.
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Able to create repeatable data load and ETL processes using python scripts. Experience with programming, technology, and tooling such as R, Python, SQL, Snowflake, Azure, Git, Informatica IICS, Tableau, Power BI, Business Objects.
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Expertise in the physics of additive manufacturing processes such as wire arc DED and laser powder DEDExpertise in physics-based simulation and its integration with machine learning models. The successful candidate will be a core team member responsible for integrating physics-informed machine learning solutions with our state-of-the-art 3D printing technologies.
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Experience with Python AWS automation - boto3, CDK, REST interface, Flask; or other relevant experience (e.g. TypeScript with CDK) Ring Data Management is seeking a self-directed System Development Engineer to develop and operate our AWS cloud data processing systems.
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6 years An equivalent of 6 years experience with big data, database query and analysis languages (e.g. Python, SQL, Snowflake SQL, R, Scala, SAS, Azure DataBricks) and data visualization tools (e.g. Power BI, Tableau) required.
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