KASHII UPDATEZ Everyday Student Requirements & Python Coding Tutorials by Python Kashi
REQUIREMENT_ID_2403 • 3-DAY_ACTIVE_POLICY JD

Associate - Data Scientist

Company
Company United
Type
Opportunity Type Full-Time Job
Salary
Stipend / Salary 6 LPA
Location
Location Gurugram, India
Posted Date
Posted Date Today
Apply on Official Website ↗ šŸ¤ Connect Recruiter ↗
UN
United Technical Recruiter
Talent Acquisition Partner
šŸ¢ United • Direct Recruiter Email: recruiter@united.com
Python R SQL Machine Learning Statistical Modeling Data Visualization GenAI LLM Prompt Engineering Multi‑modal AI Cloud (AWS/Azure) Git Communication Teamwork
šŸ“–
Aptitude and Reasoning Practice Open Resource ↗
Helps you sharpen quantitative and logical reasoning skills essential for the online assessment at United Airlines.
šŸ“–
Technical Interview Preparation Open Resource ↗
Provides curated coding problems and interview experiences that align with the technical round for data science roles.
šŸ“–
Comprehensive Interview Guides Open Resource ↗
Offers detailed interview roadmaps, sample questions, and preparation tips useful for United Airlines hiring process.
šŸ“–
Coding Practice Platform Open Resource ↗
Contains a wide range of algorithmic challenges to improve coding speed and accuracy for the assessment stage.

BTech or Bachelor’s degree in Engineering, Computer Science, Statistics, Operations Research, Applied Mathematics, Economics or related fields; 0‑3 years of experience in analytics or data science (full‑time or internship); minimum 60% academic aggregate; no active backlogs at the time of joining; strong analytical and problem‑solving abilities.

1
Round 1: Online aptitude and coding test
2
Round 2: Technical interview (ML concepts, case studies, coding)
3
Round 3: HR interview (fit, motivation, compensation discussion)
United Airlines is one of the world’s largest airlines, operating a vast network that connects more than 350 destinations across six continents. Through its Indian subsidiary, United Airlines Business Services Pvt. Ltd, the company brings global best‑practice aviation operations, technology, and customer experience to the Indian market. The organization prides itself on a culture of safety, innovation, and relentless focus on the passenger journey, offering employees the chance to work on high‑impact projects that shape the future of air travel. The Analytics and Innovation (Ai) team at United Airlines is a fast‑growing hub where data science meets business strategy. As an Associate Data Scientist, you will be part of a collaborative environment that partners with airport operations, revenue management, digital products, and many other functions. Your primary mission is to translate complex data into actionable insights, build machine‑learning models, and deploy generative‑AI solutions that drive revenue, improve customer engagement, and automate manual processes. Key Responsibilities: 1. Collaborate with cross‑functional stakeholders to gather requirements, understand business problems, and define data‑driven solutions. 2. Design, develop, and validate predictive and prescriptive models using classical ML algorithms (e.g., Random Forest, XGBoost, K‑Means) and emerging GenAI/LLM techniques. 3. Build end‑to‑end data pipelines for multi‑modal data (text, voice, image) and ensure robust model monitoring in production. 4. Prototype and ship AI‑assisted tools such as coding agents, prompt‑engineered LLM assistants, and agentic frameworks to accelerate solution delivery. 5. Conduct research on the latest advancements in deep learning, computer vision, and natural language processing, and share findings with the team. 6. Prepare clear, business‑focused presentations and visualisations to communicate insights and recommendations to senior leadership. 7. Partner with data‑engineering and operations teams to ensure seamless deployment, scalability, and maintenance of AI solutions. 8. Participate in code reviews, knowledge‑sharing sessions, and continuous improvement initiatives within the Ai team. Tech Stack: Python, R, SQL, Git, AWS/Azure cloud services, Docker/Kubernetes, ML libraries (scikit‑learn, XGBoost, PyTorch, TensorFlow), LLM frameworks (LangChain, LangGraph), prompt‑engineering tools, Tableau/PowerBI for visualisation. Growth Path: Starting as an Associate Data Scientist, you can progress to Senior Data Scientist, Lead AI Engineer, or AI Product Manager, with opportunities to lead cross‑functional projects, mentor junior talent, and influence United’s global AI strategy. Why Join United Airlines? You will work on real‑world aviation challenges, gain exposure to cutting‑edge AI technologies, and be part of a globally recognised brand that values diversity, continuous learning, and employee wellbeing. The role offers a blend of analytical rigor and creative problem‑solving, making it an ideal launchpad for a data‑science career.

United — Data Analytics & SQL Interview Guide

Previously asked questions, exam syllabus, coding benchmarks & round strategy.

APTITUDE & LOGIC šŸ“–
Aptitude Practice Questions & Online Mock Tests

Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.

Open Resource ↗
COMPANY GUIDE šŸŽÆ
United Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for United and off-campus tech roles.

Open Resource ↗
MOCK TESTS & PAPERS šŸ“
Comprehensive Interview Prep Resources & Syllabus

Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.

Open Resource ↗
CODING PRACTICE šŸ’»
Algorithm and Data Structure Problem Set

Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.

Open Resource ↗
Round 1: Online Assessment (OA)
Aptitude, Quantitative Logic & 2 Coding Problems
Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1
Core Tech Stack (Python, R, SQL, Machine Learning, Statistical Modeling, Data Visualization, GenAI, LLM Prompt Engineering, Multi‑modal AI, Cloud (AWS/Azure), Git, Communication, Teamwork) & Live Code Tracing
Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving
Database Schemas, APIs & Architecture Basics
Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion
United Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
What is the difference between WHERE and HAVING clauses in SQL? Answer ā–¼
Model Answer: WHERE filters rows before any groupings are applied, while HAVING filters aggregated groups after GROUP BY has executed.
Explain SQL Window functions: ROW_NUMBER(), RANK(), and DENSE_RANK(). Answer ā–¼
Model Answer: ROW_NUMBER() assigns unique sequential integers. RANK() assigns identical ranks to ties and skips ranks. DENSE_RANK() assigns identical ranks to ties without skipping rank numbers.
How do you handle NULL and missing values during data cleaning in Python/Pandas? Answer ā–¼
Model Answer: Use .isna().sum() to identify missing values. Impute with mean/median using .fillna() or remove with .dropna(subset=[...]) depending on variance impact.
What is the difference between Star Schema and Snowflake Schema in Data Warehousing? Answer ā–¼
Model Answer: Star Schema has denormalized dimension tables directly connected to the central Fact table. Snowflake Schema normalizes dimension tables into sub-dimensions to minimize redundancy.
How do you calculate MoM (Month-over-Month) growth in SQL? Answer ā–¼
Model Answer: Use LAG(revenue, 1) OVER (ORDER BY month) to fetch the previous month's revenue and compute (revenue - prev_revenue) / prev_revenue * 100.
Why do you want to join United as a Associate - Data Scientist?
Preparation Tip: Highlight United's market reputation, recent tech innovations, and how your skills in Python directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Preparation Tip: Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Preparation Tip: Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.

More Fresh Requirements in Software Engineering

View Category Feed ↗
United
Associate - Data Scientist
Recruiter Apply ↗
Chat Chat with Kashii