GAP

Global apparel retailer with DTC brands

Sr Analyst - Data Science

Data ScienceConfirmed live in the last 24 hours

Full-timeHyderabad, Telangana, IndiaNo salary listedIn-person

About the Job

Requirements

Advanced proficiency in R, Python, Spark, Hive or other MapReduce technologies, and common scripting languages for end-to-end pipelines.
Advanced proficiency using SQL to efficiently manipulate large datasets in on-premises and cloud distributed computing environments such as Azure.
Experience with machine learning and classical predictive techniques, including logistic regression, decision trees, nonlinear regression, artificial neural networks, convolutional neural networks, boosted trees, support vector machines, TensorFlow, and visualization packages, with a track record of creating business impact using these methods.
Ability to work at a detailed level, summarize findings, extrapolate knowledge, and make strong recommendations for change.
Ability to collaborate with cross-functional teams and influence product and analytics roadmaps, with demonstrated relationship-building proficiency.
Ability to assess relatively complex situations, analyze data, make judgments, and recommend solutions.

Responsibilities

Develop software programs, algorithms, and automated processes that cleanse, integrate, and evaluate large datasets from multiple disparate sources.
Manipulate large amounts of data across diverse subject areas and collaborate with data scientists and data engineers to prepare data pipelines for various modeling protocols.
Build, validate, and maintain artificial intelligence, machine learning, and deep learning models; diagnose and optimize performance; and develop statistical models and analyses for ad hoc business-focused analysis.
Communicate meaningful, actionable insights from large data and metadata sources to stakeholders.
Ensure quality of services and advice in meeting business partner needs.
Be responsible for team end results and share responsibility for resources, budget, and adherence to policies.

About the Role

The Customer Analytics Team at Gap Inc. applies data analysis and machine learning techniques to drive business benefits for Gap Inc. and its brands. The team’s focus is on creating analytical capabilities to support customer acquisition and retention, personalization and marketing at Gap Inc. Areas of expertise include segmentation, targeting, forecasting, marketing effectiveness measurement and optimizations, customer behaviors, site analytics and business growth initiatives. You will support the team to build and deploy Data and Analytics capabilities, in partnership with GapTech, PDM, Central Marketing & business partners across our brands.

What You'll Do

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

Who You Are

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

GAP