Data Scientist 1

Deluxe•Atlanta, GA

About The Position

Are you an analyst who enjoys working directly with clients and making a direct and verifiable impact to their business and the success of your team? Come fill that role on a growing team of data professionals serving large clients across the U.S. The Data Analyst is responsible for leading the development of data-driven solutions for our clients. The role utilizes analytical, statistical, and programming skills to clean, aggregate, and analyze large data sets and interpret results. This position requires a strong command of statistical techniques and machine learning algorithms, as well as a demonstrated practical ability to determine where to invest time, synthesize actionable findings across diverse assignments, and present findings to audiences with diverse agendas and varying levels of technical expertise

Requirements

Bachelor’s degree in Computer Science, Math, Statistics, Machine Learning, Analytic, Data Science and 0 to 2 years experience.
Must be 18 years of age or older

Nice To Haves

Masters Degree in Computer Science or Statistics
1 year in Data Science

Responsibilities

Querying, pre-processing, data cleaning, feature engineering and analyzing large amounts of structured and Unstructured data(terabytes/petabytes) across multiple data sources using structured query language(SQL), Python, Pytorch, Pyspark, R, Spark and Scala. In a Cloud Native AWS environment.
Deliver custom and commercial scalable solutions for internal and external customers.
Combine business requirements and existing processes and data knowledge to create analytical solutions by building and deploying unsupervised and supervised machine learning and deep learning models. Including combining models using ensemble modeling techniques.
Required to have knowledge and experience in unsupervised learning, principle component analysis(PCA), GLM, lasso/ridge regression, random forest, gradient boosted machines(GBM’s), XGBoost, Baysian optimization, natural language processing(NLP) and deep neural networks/ back propagation.
Use advance statistical concepts for sampling, descriptive statistics, hypothesis testing, data quality, performance testing, attribution analysis, multi variate segmentation and recommender systems.
Collaborate with other data scientists to solve demanding and complicated business problems by applying machine learning, deep learning to large data sets.
Partner with Data Engineering on product development(proof of concept to commercial product), SDLC and CI/CD pipelines to process data, train models, test predictions within a MLOPS framework all at scale and be able to provide requirements for deployment.
Must be able to work within an agile framework.