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Machine Learning Solutions Architect - Omaha

phDataOmaha, NE
Hybrid Full-time

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Experience Level

Mid to Senior

Qualifications

Candidates should have a strong background in machine learning, data science, and software engineering. Proficiency in programming languages such as Python, Java, or Scala is essential. Experience with cloud platforms like AWS, Azure, or GCP, and familiarity with data processing and management tools will be advantageous. A proven track record of deploying machine learning models in production environments is highly desirable.

About the job

Join phData, a pioneering force in the modern data landscape. We collaborate with leading cloud data platforms such as Snowflake, AWS, Azure, GCP, Fivetran, Pinecone, Glean, and dbt to provide innovative services and solutions. Our mission is to empower global enterprises to tackle their most pressing data challenges.

As a remote-first global organization, phData boasts a diverse team across the United States, Latin America, and India. We value the unique culture of each team member, fostering a community rooted in technological curiosity, accountability, and trust. Despite our rapid growth, we maintain an engaging and dynamic work environment, hiring top talent and granting you the freedom to achieve impactful results.

Recognized as a leading workplace in the US, India, and LATAM.

Machine Learning Solutions Architect - We seek a candidate located in or near Omaha, Nebraska, who can provide on-site client support approximately two weeks each month.

As a Machine Learning Engineer, you will be a versatile problem solver, equipped with the necessary tools to bring data science models to fruition. You will oversee the infrastructure and deployment plans, ensuring that data science models are successfully operationalized.

About phData

phData is a trailblazer in the modern data stack, recognized for its exceptional partnerships with major cloud data platforms. With a commitment to innovation and excellence, we empower enterprises worldwide to solve their most intricate data challenges while fostering a collaborative and vibrant work culture.

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