Expert Data Scientist

Overview
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 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 an Expert Data Scientist with a versatile skill set to undertake data science and analytics supporting the development of next-generation products for Acxiom’s business.

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

As part of the Data Science & Analytics Team, the Expert Data Scientist will work hands-on with innovative technologies to build scalable data products and solutions for our US and global businesses. The Expert Data Scientist’s responsibilities include collaborating with stakeholders to identify business requirements, leverage Acxiom’s internal and client data sources creatively, build models, analyze and visualize results, review compliance requirements, and integrate the solution into innovative data products. The Expert Data Scientist will be a champion of the latest Machine Learning and Artificial Intelligence technology stack. This role will focus on developing state-of-the-art machine learning models and solutions in the healthcare vertical.

What you will do:

Modeling:

  • Combine healthcare data, domain expertise & knowledge of machine learning and AI to develop high performant & predictive models
  • Assist with the validation and delivery of healthcare data products or enhancements
  • Apply state-of-the-art algorithms relying on knowledge of statistical modeling, machine learning, and optimization to or improve the performance/quality of existing health propensities and related data products

Product Development, Operationalization and Measurement:

  • Collaborate with product team, other data scientists to define project requirements including data sources, algorithms, and specific model implementation
  • Collaborate with internal and external stakeholders to understand business goals and product economics, and identify relevant KPIs to assess product in-market performance
  • Assist with engineering, build teams, delivery and platform teams to ensure appropriate data delivery and presentation
  • Offer ideas for product and/or process improvements such as automation related to focus area of work
  • Partner with agencies in developing closed loop measurement solutions

Quality Assessment and Governance

  • Monitor model performance and adjust models as directed by team leads and senior data scientists
  • Perform analysis, maintenance and upgradation of existing models & data products
  • Be familiar with HIPAA and data governance laws. Sustain and enhance appropriate QA processes & controls for data and process governance.

What You Will Have:

  • Bachelor’s Degree in a quantitative field (Applied Mathematics, Applied Statistics, or Computer Science) or related degree programs and/or 8-10 years of relevant work experience
  • 6+ years of working in Healthcare domain and prior experience working with healthcare data assets
  • Strong analytical acumen, ability to work with large volumes and diverse datasets to develop modeled data products
  • Self-starter, strong communication skills and ability to communicate complex AI and Machine Learning concepts to non-technical audiences.
  • Ability to leverage critical data-driven thinking and enthusiasm for translating data into actionable insights to generate consistently accurate and useful analyses and models
  • Working knowledge or experience with one or more of the following tools:  R, Python, Scala, Spark/pyspark or similar programming language
  • 7+ years’ experience in building models and applying ML Algorithms (GLM, Decision Tree, Boosting, Bagging Trees, SVM, regression, clustering etc.)
  • Expert at model training approaches, hyperparameter tuning, and model evaluation approaches
  • 7+ years of experience in deploying ML models into production applications
  • 5+ years of experience building ETL transformation, modeling & data pipelines
  • 5+ years experience in one or multiple Big Data or cloud environments (e.g. AWS, Google AI/ML Platform., Snowflake, Databricks)
  • Experience with Microsoft Excel, and PowerPoint Outstanding troubleshooting, attention to detail, and communication skills (verbal/written) in a fast paced setting
  • Solid communication skills: Demonstrated ability to explain complex technical issues to technical and non- technical audiences.

What will set you apart:

  • Knowledge of Deep Learning, Neural Network based on modeling frameworks a plus
  • Knowledge of container based model deployment (Docker, Kubernetes) as plus
  • Master’s Degree in Statistics, Data Science, Applied Mathematics, Engineering, Operations Research, or similar fields
  • At least 6 years of experience in advanced analytics techniques in a consulting/healthcare space and not solely in an academic environment
  • Experience with using tools such as Airflow, KubeFlow for model deployment a plus
  • Experience with model building using H2O or similar machine learning platforms

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