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    Data Science Engineer II - austin, United States - Vericast

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    Full time
    Description

    Job Description

    We are seeking a skilled, and creative Data Science Engineer focused on supporting the complete lifecycle of Data Science Offerings on Vericast's next-generation Marketing Platform (NXTDRIVETM). As a Data Science Engineer, you will play a pivotal role in implementing, optimizing, and benchmarking our machine learning models on the platform. You will collaborate closely with data scientists, contributing to all phases of data science projects, and ensuring seamless integration between engineering and data science efforts. This role will work cross-functionally with data science, engineering, product, and IT stakeholders in an agile framework.

    Key Duties & Responsibilities

  • Develop and deploy highly scalable and distributed machine learning systems AWS. 10%
  • Fine-tune existing PySpark jobs and processes for optimal performance. 10%
  • Implement various modeling techniques, including descriptive, predictive, and prescriptive models, at scale. 10%
  • Design, construct, and QA data pipelines that power machine learning models. 10%
  • Generate test and validation data sets to ensure rigorous model testing and validation. 10%
  • Devise and implement effective methodologies for data manipulation and vectorization. 10%
  • Provide comprehensive engineering support to data scientists throughout the lifecycle of data science projects. 10%
  • Enhance and benchmark existing machine learning models by integrating new data sources. 10%
  • Perform quality assurance and troubleshoot production data pipelines for machine learning services. 10%
  • Participate actively in all scrum events to foster collaboration and iterative development. 10%

    Qualifications:
    Qualifications
  • Master's Degree in Computer Science or equivalent technical field (Required)
  • In lieu of the above education requirements, a combination of experience and education will be considered.
  • Over 2 years of hands-on experience with AWS.
  • 2- 3 years of software development experience using Python and Spark in practical industry settings.
  • Demonstrated expertise in tuning PySpark or Scala-based Spark jobs for performance optimization.
  • Proficiency in building Data Pipelines on AWS, with at least 2 years of experience.
  • At least 2 years of experience building Predictive or Prescriptive Machine Learning Models.
  • Minimum 1 year of hands-on experience with AWS Sagemaker.

    Knowledge/Skills & Abilities
  • Strong understanding of Machine Learning workflows and methodologies.
  • Agile experience.
  • Ability to excel in a fast-paced, collaborative team environment.
  • Skilled in creating clear, data-driven presentations and reports suitable for both technical and non-technical stakeholders.
  • Excellent active listening skills to facilitate effective communication and collaboration.
  • Quick adaptability to a wide array of open-source technologies and tools.

    Additional Information
    Salary:$115,000-125,000
    The ultimate compensation offered for the position will depend upon several factors such as skill level, cost of living, experience, and responsibilities.
    Vericast offers a generous total rewards benefits package that includes medical, dental and vision coverage, 401K and flexible PTO. A wide variety of additional benefits like life insurance, employee assistance and pet insurance are also available, not to mention smart and friendly coworkers
    At Vericast, we don't just accept differences - we celebrate them, we support them, and we thrive on them for the benefit of our employees, our clients, and our community. As an Equal Opportunity employer, Vericast considers applicants for all positions without regard to race, color, creed, religion, national origin or ancestry, sex, sexual orientation, gender identity, age, disability, genetic information, veteran status, or any other classifications protected by law. Applicants who have disabilities may request that accommodations be made in order to complete the selection process by contacting our Talent Acquisition team at EEO is the law. To review your rights under Equal Employment Opportunity please visit:

    #LI-TE1

    #LI-remote



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