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    Lead Machine Learning Data Engineer - St Louis, United States - FleishmanHillard

    FleishmanHillard
    FleishmanHillard St Louis, United States

    1 week ago

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    Description
    Overview


    Are you fascinated by the power of marketing on culture and society? Do you have an insatiable appetite to learn and build new things? Does the idea of innovating the marketing industry bring out the scientist AND the artist in you? If you're excited about seeing your work come to life across the many faces of the internet, then read on.

    Methods+Mastery has an immediate opening for a talented engineer to work on Fortune 50 tech brands. This position offers the opportunity for a hybrid set-up with work-from-home and work-from-office flexibility.

    Our ideal candidate is a born collaborator with excellent communication skills and solid machine-learning fundamentals.

    We are a close-knit team that takes huge pride in the work we produce, and our new machine learning data engineer will be key in taking that work to the next level.

    To be successful, you must possess a voracious appetite to learn, grow, work hard, and have fun.

    If you are curious and inventive and are someone who is not afraid to push the boundaries of marketing science and drive our clients to new levels of innovative thinking, we encourage you to apply.


    Methods+Mastery is an entrepreneurial, collaborative environment that values talented, creative people who like to work with others to create cutting-edge programs for our clients.

    We work on projects ranging from regional to global in scope for some resume-bolstering brands.

    If you'd like to hang, you'll have the opportunity to contribute against the full spectrum of marketing science work we do, such as building custom NLP models, time series forecasting and predictive modeling, causality testing, and automating methodologies and processes so that we can do things better and faster.


    Methods+Mastery is actively committed to increasing our team's diversity, aggressively eliminating systemic barriers to equity, and fostering a culture where different backgrounds and perspectives are respected and celebrated.

    We firmly believe a team of many diverse perspectives not only makes M+M a better place to work, it is also critically important for producing creative and thoughtful work that represents the world we live in.

    To that end, we strongly encourage applications from women, people of color, members of the LGBTQ+ community, veterans, individuals with disabilities, and neurodivergent people.

    The anticipated salary range for this position is $165,000 - $220,000.

    Salary is based on a range of factors that include relevant experience, knowledge, skills, other job-related qualifications, and geography. A range of medical, dental, vision, 401(k) matching, paid time off, and/or other benefits also are available.

    Responsibilities

    Collaborate with cross-functional teams, including analysts and clients, to identify business requirements and translate them into technical solutions for an internal intelligence team of media analysts to measure how earned media and social media impact a client's brand and reputation

    Design, develop, and maintain ETL pipelines to extract, transform, and load data from various sources using tools like Dataflow, Cloud Run, and Cloud Functions

    Build and deploy containerized applications for data processing and machine learning using technologies such as Docker, Kubernetes, and Kubeflow

    Optimize and scale machine learning workflows using cloud platforms like Google Cloud Platform (GCP)

    Create and maintain documentation for data pipelines, machine learning models, and related processes

    Optimize data storage and retrieval using databases like PostgreSQL and MySQL

    Develop and implement machine learning models to solve complex problems in the PR and marketing domains, such as sentiment analysis, customer segmentation, and campaign optimization

    Conduct model evaluation, validation, and testing to ensure the accuracy, reliability, and performance of machine learning models

    Design and build data visualization dashboards using tools like Looker Studio (formerly Google Data Studio) to provide insights and support data-driven decision-making

    Implement data quality checks and monitoring systems to ensure data integrity and reliability throughout the data lifecycle

    Collaborate with multiple stakeholders to establish best practices for data management, security, and governance, including data security measures and compliance with data privacy regulations such as GDPR and CCPA

    Qualifications


    Must-haves:
    5+ years of experience working as a Machine Learning Data Engineer, or in Data Science

    5+ years of experience with Machine Learning, Forecasting, Computer Vision, and/or Natural Language Processing (NLP)

    5+ years of experience working with major machine-learning Python libraries (Scikit-learn, PyTorch, Tensorflow, etc.)

    1-2 years of independently developing project plans and managing junior team members

    Experience with GCP and Google's suite of data tools

    Well-versed in full development life cycle - understanding of backend development, continuous integration, and continuous deployment

    Experience dashboarding and creating visuals

    Experience working with stakeholders & gaining client buy-in

    Experience with team management and running projects

    Ability to handle the ambiguity of juggling multiple projects, deadlines, and evolving client priorities

    Ability to explain highly technical concepts to technical and non-technical audiences

    Excellent written and verbal communication skills


    Nice to haves:
    Experience working with social media, paid media, or earned media data

    Experience working for a consulting firm

    Experience working with Large Language Models and Prompt engineering (ChatGPT, Gemini or RAG)

    #LI-DNI
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