Data Scientist - Digital Data Products (Remote)

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

At Acxiom, our vision is to transform data into value for everyone. Our data products and analytical services enable marketers to recognize, better understand, and then deliver highly applicable messages to consumers across any available channel. Our solutions enable true people-based marketing with identity resolution and rich descriptive and predictive audience segmentation. We are seeking a Data Scientist with a versatile skill set to undertake data science supporting the development of next-generation digital data product.

As part of the Data Science and Analytics Team, the Data Scientist will lead the charge in developing machine learning and statistical models to support and expand the Audience Propensities product suite for our domestic and global businesses. The Data Scientist’s responsibilities will include 1) partnering with product, engineering and business stakeholders to define digital product scope and requirements, 2) building models, analyzing/visualizing the results and integrating the solution into our suite of data products, 3) developing new analytical reports to help us better understand our data. The Data Scientist will be a champion of the latest Machine Learning and Artificial Intelligence technologies and will not only be an advocate but will also lead by example in influencing adoption.

This role can be located almost anywhere in the U.S.

What you will do:

• Build expert knowledge of the various data sources brought 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 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 concepts to marketing and business audiences

What you will need:

• 2+ years of leveraging data science and modeling methods. Experience in AdTech/MarTech space is a plus.
• Atleast 1+ years of experience working with digital marketing datasets will be a plus
• Experience with applying statistics and data science tools on large datasets. Extensive experience with data preparation (normalization, scaling, etc.) for modeling
• 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
• 3+ 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 2+ years of experience building ETL transformation, SQL, modeling & mlops pipelines
• 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 4+ years of relevant work experience OR Master’s Degree in a quantitative field and 1+ years relevant work experience

What will set you apart:

• Exposure to E2E ML platform such as 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 1-year experience in leveraging Deep Learning, Neural Network based modeling frameworks (Tensorflow, Keras)
• At least 1 year of experience deploying data/analytical products at scale using Cloud technologies e.g. AWS Sagemaker, Google Cloud Platform, etc.)