Local Team Lead
hace 1 mes
Location: Lomas Atlas, Mexico City, MX
Duties and Responsibilities
Build expert knowledge of the various data sources together for audience propensities solutions – survey/panel data, 3rd-party data (demographics, psychographics, lifestyle segments), media content activity (TV, Digital, Mobile, Automotive), and product purchase or transaction data
Apply state-of-the-art algorithms relying on knowledge of statistical modeling, machine learning, and optimization to develop new audience propensities & analytical data products or improve the performance/quality of existing audience propensities and data products
Build, evaluate and optimize models which incorporate machine learning and artificial intelligence
Be a thought leader and champion for adoption of new technologies and enable migration to new cloud based ML stack
Collaborate with internal and external stakeholders to understand business goals and product economics, and identify relevant KPIs to assess product in-market performance
Work with other Applied and Data scientists and team leads to define project requirements including data sources, algorithms, and implementation
Partner with Product and Engineering teams to transition development projects to production systems
Effectively communicate complex data science/ML concepts to marketing and business audiences
Qualifications
Experience Required
Proficient English writing and speaking
Very strong data science / machine learning experience.
5+ years of leveraging data/applied science and modeling methods.
Experience with Pyspark, AWS Infrastructure and MLOps
Experience with applying statistics and data science tools on large datasets.
Extensive experience with data preparation (normalization, scaling, etc.) for modeling
5+ years of experience in building, testing and deploying production ready models in python, R, spark, Julia or similar languages and experience using Scikit learn, MLlib or similar packages
At least 3+ years of experience building ETL transformation, SQL, modeling & mlops pipelines
Working knowledge of supervised vs. unsupervised learning algorithms, including linear/logistic regression, neural networks/deep learning techniques, SVM, decision trees (bagging, random forests, boosting), XG Boost, clustering, regression, and dimensionality reduction techniques
Strong skills on model training approaches, hyperparameter tuning, and model evaluation approaches
Ability to leverage critical data-driven thinking and translating data into actionable insight to generate consistently accurate and useful analysis and models
Attention to detail and time management delivering high quality work for multiple projects across several engagements while meeting deadlines
Bachelor’s Degree in a quantitative field (Data Science, Statistics, Math) or a related degree program and 5+ years of relevant work experience OR Master’s Degree in a quantitative field and 3+ years relevant work experience
What will set you apart
Experience with E2E ML platform such as H20, Databricks, AWS Sagemaker, Google AI/ML platform
Experience with using tools such as Airflow, KubeFlow for model deployment will be a plus
CI/CD/MLOps experience - container-based model deployment frameworks using (Kubernetes, Docker, ECS/EKS or similar) will be a plus
At least 2+ years experience in leveraging Deep Learning, Neural Network based modeling frameworks (Tensorflow, Keras)
At least 2+ years of experience deploying data/analytical products at scale using Cloud technologies e.g. AWS Sagemaker, Google Cloud Platform, etc.)
At least 2+ years of experience working with digital marketing datasets will be a plus
Experience in AdTech/MarTech space is a plus.
Primary Locations:
Mexico CityAdditional Locations (if applicable):
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