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This role is very dynamic and diverse requiring specific analytic, mathematic, programming, and statistical skills utilized in the execution of data and statistical modeling; analytic solutions and reporting for both online and offline B2C and B2B customers. This role can be located almost anywhere in the U.S.
WHAT YOU WILL DO:
We are looking for a well-rounded Data Scientist that has an academic background in statistics as well as hands-on Machine Learning experience. We are looking to find someone who can be an advocate (both within Acxiom and with our clients) for applying Machine Learning approaches to marketing challenges, primarily predictive analytics and/or segmentations. WHAT YOU WILL HAVE:
- Bachelor’s or graduate degree in statistics/computer science or related field plus 5 yrs. experience.
- End-to-end experience developing approach/methodology given business need, ETL, data quality analysis, model development and validation (machine learning/statistical), scoring, presentation of results, and deployment into production environment (including AWS, Azure, Google Cloud).
- Strong experience with predictive models and clustering (segmentation).
- Strong/Expert SQL, Python, R, SAS across a variety of environments.
- Experience with Tableau, Looker, Microsoft Excel, and PowerPoint a plus.
WHAT WILL SET YOU APART:
- Strong team player, flexible, and creative
- Experience with marketing related analytics/channels/metrics, especially digital
- Passion/Curiosity around new techniques, i.e. deep learning
- Identity resolution experience, data with multiple levels and sources – aggregating & connecting
- Ability to learn and lead with minimal oversight, work on several projects at same time
- Strong communication and presentation skills, ability to maintain timeline (stay on task)
/#GD17 PRIMARY LOCATION CITY/STATE: Homebased – Conway, Arkansas
Acxiom is an affirmative action and equal opportunity employer (AA/EOE/W/M/Vet/Disabled) and does not discriminate in recruiting, hiring, training, promotion or other employment of associates or the awarding of subcontracts because of a person’s race, color, sex, age, religion, national origin, protected veteran, military status, physical or mental disability, sexual orientation, gender identity or expression, genetics or other protected status.