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REQUIREMENT_ID_226 β€’ 3-DAY_ACTIVE_POLICY

Data Analyst - Revenue Ops

Company
Company Arcadia
Type
Opportunity Type Internship
Salary
Stipend / Salary USD 70,000 - 90,000 per annum
Location
Location Remote
Posted Date
Posted Date Today
Advanced Excel SQL Python Data cleaning Data visualization Analytical thinking Communication Problem solving Attention to detail Basic knowledge of energy billing
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Aptitude Practice Questions Open Resource β†—
Helps you sharpen quantitative and logical reasoning skills required for the initial screening test.
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Company Interview Corner Resources Open Resource β†—
Provides general interview preparation tips and common question patterns useful for Arcadia’s technical rounds.
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Arcadia Data Analyst Preparation Guide Open Resource β†—
Specific insights, sample questions, and role‑specific topics to help you ace the Data Analyst interview at Arcadia.
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Algorithm & Data Structure Problem Set Open Resource β†—
Offers coding practice to strengthen Python problem‑solving abilities often tested in technical assessments.

Graduates (B.Tech/B.E., B.Sc., B.Com, MBA) in Computer Science, Information Technology, Statistics, Economics, Finance or related fields; minimum 60% aggregate (or CGPA 6.0/10); batch year 2025‑2027; no active backlogs; strong analytical and communication skills; willingness to work remotely in the US time zones.

1
Round 1: Online aptitude & logical reasoning test
2
Round 2: Technical interview (SQL/Python & case study)
3
Round 3: HR interview (culture fit, compensation discussion)
Arcadia is an AI‑powered energy intelligence platform that helps enterprises manage utility bills, procure energy, and report sustainability metrics on a single, unified platform. By replacing fragmented tools and manual workflows, Arcadia enables Fortune 2000 companies to automate the entire utility bill lifecycle, leverage data‑driven procurement strategies, and integrate verified emissions data into leading sustainability solutions. The company’s mission is to simplify energy management, drive cost savings, mitigate risk, and accelerate the transition to a low‑carbon future. With a strong focus on innovation, Arcadia combines large‑scale data aggregation, advanced analytics, and expert advisory to deliver measurable business value across thousands of locations worldwide. The Data Analyst – Revenue Ops role sits within the Revenue Operations team and is responsible for turning raw energy and billing data into actionable insights for customers and internal stakeholders. The analyst will work closely with product, engineering, finance, and customer success teams to ensure data accuracy, build reporting pipelines, and support decision‑making that improves revenue performance and customer satisfaction. This position is ideal for recent graduates who are comfortable with Excel, have a knack for SQL or Python, and are eager to learn the nuances of the energy‑billing domain. Key Responsibilities: 1. Gather, cleanse, and validate utility billing data from multiple sources to ensure high‑quality datasets. 2. Build and maintain automated reporting dashboards using Excel, Power BI or similar tools. 3. Write and optimize SQL queries to extract, transform, and load data for revenue analysis. 4. Collaborate with cross‑functional teams to define data requirements and translate business questions into analytical solutions. 5. Monitor key performance indicators (KPIs) related to revenue, billing accuracy, and customer onboarding timelines. 6. Identify data anomalies, troubleshoot issues, and coordinate escalations with engineering or operations as needed. 7. Prepare regular performance reports and ad‑hoc analyses for senior leadership and external customers. 8. Contribute to process improvement initiatives by documenting workflows and recommending automation opportunities. 9. Support the development of predictive models for revenue forecasting using Python or R (optional but advantageous). 10. Participate in customer calls to explain data insights and gather feedback for continuous improvement. Tech Stack: MS Excel (advanced pivots, formulas), SQL (PostgreSQL/MySQL), Python (pandas, numpy), Power BI/Tableau, Git for version control, and familiarity with cloud data warehouses (Snowflake, BigQuery) is a plus. Growth Path: Starting as a Data Analyst, high performers can progress to Senior Analyst, Revenue Operations Manager, or specialize into Data Engineering or Business Intelligence roles within Arcadia’s fast‑growing analytics organization. Why Join Arcadia? The company offers a remote‑first culture that lets you work from anywhere in the continental US, flexible PTO, comprehensive health benefits, and a strong emphasis on diversity and inclusion. Employees gain exposure to cutting‑edge AI‑driven energy solutions, work alongside industry experts, and have clear pathways for professional development and leadership. Overall, this role provides a unique blend of data analytics, energy industry exposure, and a supportive, growth‑focused environment that is perfect for ambitious freshers looking to launch their careers in a high‑impact tech company.

Arcadia β€” Data Analytics & SQL Interview Guide

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

APTITUDE & LOGIC πŸ“–
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 β†—
COMPANY GUIDE 🎯
Arcadia Interview Preparation Corner

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

Open Resource β†—
MOCK TESTS & PAPERS πŸ“
Comprehensive Interview Prep Resources & Syllabus

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

Open Resource β†—
CODING PRACTICE πŸ’»
Algorithm and Data Structure Problem Set

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

Open Resource β†—
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 (Advanced Excel, SQL, Python, Data cleaning, Data visualization, Analytical thinking, Communication, Problem solving, Attention to detail, Basic knowledge of energy billing) & 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
Arcadia 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 β–Ό
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 β–Ό
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 β–Ό
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 β–Ό
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 β–Ό
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 Arcadia as a Data Analyst - Revenue Ops?
Preparation Tip: Highlight Arcadia's market reputation, recent tech innovations, and how your skills in Advanced Excel 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.

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