Senior Data Science Analyst at ELSA, focusing on data - driven strategies and customer analytics. Collaborating with teams to optimize B2C and B2B initiatives in a hybrid working environment.
About the role
- Data Scientist driving analytics and machine learning solutions for Gap Inc. Collaborating across teams to build and deploy data capabilities and influence business outcomes.
Responsibilities
- Develop software programs, algorithms and automated processes that cleanse, integrate and evaluate large data sets from multiple disparate sources
- Manipulate large amounts of data across a diverse set of subject areas, collaborating with other data scientists and data engineers to prepare data pipelines for various modeling protocols
- Build, validate, and maintain AI (Machine Learning (ML) /Deep learning) models, diagnose and optimize performance and develop statistical models and analysis for ad hoc business focused analysis
- Communicate meaningful, actionable insights from large data and metadata sources to stakeholders
- Responsible for quality of services and advice in meeting business partner needs
- Responsible for end results of team and shares responsibility over resources, budget and adherence to policies
Requirements
- Advanced proficiency in R, Python, Spark, Hive (or other MR), and common scripting languages for E2E pipeline
- Advanced proficiency using SQL for efficient manipulation of large datasets in on prem and cloud distributed computing environments, such as Azure environments
- Experience with ML and classical predictive techniques such as logistic regression, decision trees, non linear regressions, ANN/CNN, boosted trees, SVM, Tensorflow, visualization packages, and a track record for creating business impact with these methods
- Ability to work both at a detailed level as well as to summarize findings and extrapolate knowledge to make strong recommendations for change
- Ability to collaborate with cross functional teams and influence product and analytics roadmap, with a demonstrated proficiency in relationship building
- Ability to assess relatively complex situations and analyze data to make judgments and recommend solutions
Benefits
- Health insurance
- 401(k) matching
- Paid time off
- Flexible work arrangements
- Professional development opportunities
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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