Data Scientists in the Sam’s Club Technology division specialize in applying machine learning and artificial intelligence to solve problems across Merchandising, Marketing, Club Operations, Finance, eCommerce, and Security. You will have the opportunity to work with a high caliber team from a variety of disciplines to build new software and radically change our business. Data Scientists work as part of an Experience Team to develop and deploy advanced algorithms at scale. You will support and enable the entire project lifecycle including problem discovery with business clients, algorithmic design, coding, validation, deployment, testing, and monitoring. Data Scientists adhere to agile software development standards through rapid prototyping, iterative development, and incremental deployment of capabilities. Development is performed in Sprints and Data Scientists are held accountable to engineering excellence standards.
- Performs research and applies new techniques and concepts to solve problems
- Understands and translates business and functional needs into AI/ML problem statements
- Develops custom ML models to drive innovative business solutions
- Manages and integrates complex data sets from multiple, disparate data sources
- Writes complex queries and extracts data to build robust data pipelines
- Collaborates with Engineering teams to integrate algorithms into tools, processes, and interfaces
- Performs exploratory data analysis and develops models to identify trends and opportunities
- Builds and deploys reusable services and utilities that can be leveraged by a wide range of applications
- Applies innovative and scientific approaches to augment and automate business decisions
- Proficiency in machine learning algorithms such as multi-class classifications, decision trees, support vector machines, deep learning, and anomaly detection
- Strong understanding of probability and statistical models (generative and descriptive models)
- Ability to run experiments scientifically and analyze results
- Ability to effectively communicate technical concepts and results to business audiences in a comprehensive manner
- Ability to collaborate effectively across multiple teams and stakeholders, including analytics teams, development teams, product management and operations
- 1-3 years’ experience in building ML based models in a professional environment
- Computer Science fundamentals in algorithms, data structures and functional programming
- Experience with Big Data processing (Spark/Bigquery / Hive/ Hadoop/ HDFS)
- Experience with productionizing Machine Learning solutions
- Comfort level with cloud computing (e.g. Azure, Google, etc.)
- Experience with large-scale technologies (Hadoop, BigQuery, Spark, Databricks, etc.)
- Experience with anomaly detection methods and working with imbalanced data sets
- Strong background in Statistics
- Familiarity with Deep Learning algorithms
- Proficiency in coding (Python, R, C/C++, Java)
- Scripting skills in at least one of the following: Shell, Perl, Python, Bash, or Ruby
- Experience with Performance Engineering including testing, tuning, and monitoring tools.
Data science, machine learning, optimization models, Master’s degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, using open source frameworks (for example, scikit learn, tensorflow, torch)
Working virtually this year has helped us make quicker decisions, remove location barriers across our global team, be more flexible in our personal lives and spend less time commuting. Today, we are reimagining the tech workplace of the future by making a permanent transition to virtual work for most of our team. Of course, being together in person is an important part of our culture and shared success. We’ll collaborate in person at a regular cadence and with purpose.
Benefits & Perks
Beyond competitive pay, you can receive incentive awards for your performance. Other great benefits include 401(k) match, stock purchase plan, paid maternity and parental leave, PTO, multiple health plans, associate discounts, and much more!
Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.
Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2
years’ experience in an analytics or related field.
Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field.
Option 3: 4 years’ experience in an analytics or related field.
Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.
Data science, machine learning, optimization models, Master’s degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch)
Bachelors: Analytics, Bachelors: Economics, Bachelors: Mathematics, Bachelors: Statistics, Doctorate: Analytics, Doctorate: Mathematics, Doctorate: Statistics, Masters: Analytics, Masters: Economics, Masters: Mathematics, Masters: Statistics