Machine Learning Engineer (NJ)

Mid / Senior

|

Remote

Meytier Premier Employer

Working there

About This Workplace

Meytier Partner

As a Machine Learning Engineer, you will apply strong expertise in AI through the use of machine learning, data mining, and information retrieval to design, prototype, and build next generation advanced analytics engines and services. You will collaborate with cross-functional teams and business partners to define the technical problem statement and hypotheses to test. You will develop efficient and accurate analytical models which mimic business decisions and incorporate those models into analytical data products and tools. You will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.

Key Responsibilities

  • Collaborate with business partners to develop innovative solutions to meet objectives utilizing cutting edge techniques and tools
  • Create repeatable, interpretable, dynamic and scalable models that are seamlessly incorporated into analytic data products
  • Reviewing .py files to decipher business logic and process flow
  • Design and optimize scalable machine learning solutions
  • Build production ready machine learning platforms
  • Provide production support and troubleshooting
  • Provide technical leadership and influence data-driven optimization efforts
  • Engineer features by using your business acumen to find new ways to combine disparate internal and external data sources
  • Effectively communicate the analytics approach and how it will meet and address objectives to business partners

Requirements

  • Bachelors Degree in Data Science, Computer Science, Engineering, Statistics and 5+ years of experience working on Data Science and Data Engineering projects
  • Strong engineering skills in Python, Spark, Pyspark, SQL; ability to decipher complex Pyspark codes
  • Experience with Relational databases with multidimensional structures
  • Experience with large interconnected code repositories, and working on projects spread across multiple .py documents
  • Ability to write production code in Python and Scala; writing complex SQL queries and ML specific production codes on Sklearn, Spark ml, Tensorflow etc.
  • Hands-on experience in Hive and PySparkand open source tools such as kafka, bigquery etc.
  • Great command on machine learning concepts and algorithms which works on the big data world. Ability to implement ML best practicesfor the entire Data Science lifecycle
  • Proficiency with Machine Learning concepts and modeling techniques to solve problems such as clustering, classification, regression, anomaly detection, simulation and optimization problems on large scale data sets.
  • Extensive data modeling and data architecture skills
  • Exceptional communication and collaboration skills to understand business partner needs and deliver solution

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