Intern
Marque: Victoria's Secret
Emplacement: Bangalore, Karnataka, IN
Domaines d’emploi: Internship
Type d’emploi: Full-time
Job ID: 04K5H
INTERN DATA SCIENTIST
The intern data scientist will work with a data science mentor and play a key technical role in analysing large data sets to develop custom models and algorithms to drive business solutions. The projects the interns shall be working on are core retail problems spanning across few key areas. A select few problem statements:
Project 1 Title: Supply Chain Cost Optimization
Description: Predictive cost modeling by Forecasting landed costs using data & images, historical data and macroeconomic indicators; Identify cost anomalies across similar styles to flag negotiation opportunities or errors.
Required Skills & Traits: ML/DL algorithms, python/sql programming, data science introduction
Expected Outcomes: Optimize cost
Project 2 Title: Customer Forecasting
Description: Predict customer file and guide marketing investments and campaign decision planning based on traffic trends by different marketing drivers \
Required Skills & Traits: ML/DL algorithms, python/sql programming, data science introduction
Expected Outcomes: customer file forecast outputs along with interpretable drivers for scenario planning
Project 3 Title: Customer Lifecycle Modeling – Next Best Action Models
Description: Build customer lifecycle state models through a set of next best actions to increase customer retention, cross-category penetration, trip frequency and omni-channel shopping.
Required Skills & Traits: ML/DL algorithms, python/sql programming, data science introduction
Expected Outcomes: Next best action model developed and productionized; model outputs leveraged for customer journey campaigns
Project 4 Title: Supply Chain Forecasting & optimization
Description: Develop state-of-the art forecasting models at sku level to help DC teams in inventory planning and fulfilment forecasts; build optimization algos.
Required Skills & Traits: ML/DL algorithms, python/sql programming, data science introduction
Expected Outcomes: model developed and productionized; model outputs leveraged for supply chain decision planning
Project 5 Title: Agentic AI Use cases
Description: Build Agentic AI applications for the enterprise; end-to-end application build using state-of-the art llm models
Required Skills & Traits: LLMs, Prompt engineering & finetuning, LLM Evaluations, LLMOps
Expected Outcomes: Agentic AI application live
ROLES AND RESPONSIBILITIES
An Intern Data Scientist will work very closely with a data science mentor and would be responsible for building data science and machine learning/deep learning solutions for our business problems across e commerce, finance, store operations, logistics and supply chain:
• Research and propose innovative statistical/ML/DL models to address the requirements.
• Target and formulate various problems in terms of key business metrics and measure the impact of the built ML/DL techniques.
• Analyze data for trends & patterns and interpret data with a clear objective in mind.
• Develop, deploy ML/DL models in production or help develop a platform to facilitate the same.
• Work closely with the Engineering team to take Data Science projects to production.
• Communicate progress/findings to relevant stakeholders.
• Keep updated with emerging technologies in AI/ML.
SKILLS AND EXPERIENCE
Knowledge of the foundations of machine learning and statistics. Familiarity with statistical methods such as hypothesis testing, forecasting, time series analysis, etc. (Required).
• Experience with SQL, Python (Required). Experience with PySpark, Snowflake and Rest/Fast APIs (Preferred)
• Experience in Machine Learning, Deep Learning or Engineering aspects of ML model deployment (Required).
• Has or pursuing Bachelor’s/Master’s/PhD degree in Computer Science, Statistics, Applied Mathematics, or related discipline (Preferred)
• Experience of working on optimization problems – linear/nonlinear programming, (meta)heuristics for solving optimization problems (Preferred)
• Proficiency in data analysis, mathematics/probability, and statistical analysis (Required). Past Data Science project experience (Preferred)
• Should be comfortable multitasking and working in a dynamic, fast paced environment.
• Effective communication of DS requirements and dissemination of right knowledge to relevant stakeholders
• Most importantly, an inquisitive mind, an ability for self-learning and abstraction along with a risk appetite for experimentation and failure.
