AI Engineer (Remote) at Thermo Fisher Scientific #vacancy #remote

Work Schedule

Other

Environmental Conditions

Office

This is a 100% remote position. Candidate of choice must be located in the United States.

Summarized Purpose: 

Drives analytics modeling based on exploratory data analysis through application of statistics, machine learning, programming, data modeling, simulation, and/or mathematics to recognize patterns, find opportunities, and generate valuable predictive business insights in support of innovative business decisions. Supports organization leadership through data-driven decision validation and support. Qualifications:

Education and Experience: Bachelor’s degree or equivalent and relevant formal academic / vocational qualification Previous experience that provides the knowledge, skills, and abilities to perform the job (comparable to 2+ years). In some cases, an equivalency, consisting of a combination of appropriate education, training, and/or directly related experience, will be considered sufficient for an individual to meet the requirements of the role.

Knowledge, Skills, and Abilities:

  • Proficiency in applying statistics, programming, data modeling, simulation, and advanced mathematics to business questions, with a specific focus on Generative AI.
  • Expertise in exploratory data analysis techniques, machine learning algorithms (including generative models), model validation techniques, and data visualization techniques.
  • Strong knowledge in technical areas such as Snowflake, AWS EMR, Python, Spark, Shiny, Jupyter, and associated packages and libraries, specifically tailored to Generative AI.
  • Exposure to modern cloud architectures, including NoSQL databases, lambda functions, Kafka, SageMaker, TensorFlow, etc., and their utilization in Generative AI workflows.
  • Proficiency in data engineering techniques, including data pipelining, data wrangling, and data preprocessing, specifically tailored to support Generative AI workflows.
  • Strong familiarity with data management approaches, including relational databases, data schemas, object stores, column stores, triple stores, graph stores, and/or document stores, with an emphasis on managing data relevant to Generative AI.
  • Proven ability to deliver accurate work products in a cross-functional matrix environment while managing multiple competing priorities.
  • Strong analytical skills, demonstrated proficiency in developing detailed analysis, models, plan calculations, and tools, with a specific focus on Generative AI applications.

Management Role: No management responsibility

Working Conditions and Environment:

  • Work is performed in an office environment with exposure to electrical office equipment.
  • Occasional drives to site locations with occasional travel both domestic and international.

Physical Requirements:

  • Frequently stationary for 6-8 hours per day.
  • Repetitive hand movement of both hands with the ability to make fast, simple, repeated movements
  • of the fingers, hands, and wrists.
  • Frequent mobility required.
  • Occasional crouching, stooping, bending and twisting of upper body and neck.
  • Light to moderate lifting and carrying (or otherwise moves) objects including luggage and laptop
  • computer with a maximum lift of 15-20 lbs.
  • Ability to access and use a variety of computer software developed both in-house and off-the-shelf.
  • Ability to communicate information and ideas so others will understand; with the ability to listen to
  • and understand information and ideas presented through spoken words and sentences.
  • Frequently interacts with others to obtain or relate information to diverse groups.
  • Works independently with little guidance or reliance on oral or written instructions and plans work
  • schedules to meet goals. Requires multiple periods of intense concentration.
  • Performs a wide range of variable tasks as dictated by variable demands and changing conditions
  • with little predictability as to the occurrence. Ability to perform under stress. Ability to multitask.
  • Regular and consistent attendance.

Percent Billable: 0% – 20%

statistics Analytical skills data-management Apache Spark Data Engineering Apache Kafka Amazon EMR data-preprocessing snowflake-cloud-data-platform remote work validation data-modeling Machine Learning jupyter Amazon SageMaker Software Developer GenAI mathematics Python simulation data-visualization modeling shiny Analytics TensorFlow RDBMS NoSQL

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