GROWTH

Data Science Consultant

SCL | MEX | MAD

The job

As a Data Science Lead Consultant you will be part of the development and growth of the area. You’ll be responsible not only for porting Analytics capabilities to Raven and working on data-related projects, but you will be part of developing our clients to better understand their data and be the enabler for the creation of true data-driven organizations.

Responsibilities

    As a Data Science Lead Consultant, you will take part in the company development on multiple topics and missions, such as:

    • Develop proposals and strategies to address challenges and opportunities for our clients, from the perspective of data use.
    • Advise clients, create proofs of concepts and implement solutions around machine learning, advanced analytics and big data problems.
    • Help clients integrate traditional structured data with unstructured data.
    • Understand a customer's data ecosystem to understand what is available, what is missing, and where to find and collect that information to enable use cases.
    • Run sprints / validate concepts / show immediate impact of data.
    • Advice on advanced analytical and quantitative tools and modeling techniques to obtain business insights, solve complex business problems and improve decisions.
    • Develop segmentation, prediction and recommendation models with Machine Learning algorithms.
    • Present information using data visualization tools.
    Profile Requirements
    • We focus (but do not constraint) our search on professionals with a degree in Business Administration, Economics, Industrial Engineering, Marketing, and Communication. Masters is a plus.
    • Digital and technology enthusiast.
    • You are energetic, autonomous and rigorous.
    • Your ideal work experience would be 1 to 5 years.
      Skills / Experience
      • Ability to build successful relationships with clients and stakeholders.
      • Mastery of problem solving and solutioning.
      • Minimum 3-4 years of experience working in Data Analytics.
      • Methodology and process of creating statistical models (eg Propensity, Segmentation, Decision tree, LTV).Machine Learning tools and languages ​​(eg Python, R, SAS, Alteryx).
      • Experience using specialized machine learning libraries, e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc.
      • Must demonstrate the ability to visualize, understand, and implement new techniques related to ML and AI as they evolve.
      • Experience in the use of Cloud technologies, for example. AWS, GCP, or Azure.
      • Specialized visualization techniques, eg. D3.js, ggplot, etc.
      • Verbal/written communication skills and data presentation skills and business proposals.
      • Have previous consulting experience (desirable).

        Working days

        Full Time

        Modality

        Hybrid/remote

        Antiquity

        2 years

        Seniority

        Semi senior

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