Data Analyst / Data Scientist

The interview process at Docs.google.com typically starts with an online coding test focusing on SQL queries and Python data‑manipulation tasks. Successful candidates move to a technical interview where they solve case‑study problems, discuss machine‑learning concepts and demonstrate analytical thinking. The final HR round assesses cultural fit, communication skills and career aspirations. Overall difficulty is moderate to high, and thorough preparation on data‑science fundamentals and problem‑solving is key.

Round 1: Online assessment (SQL & Python coding) → Round 2: Technical interview (case studies, ML concepts, problem solving) → Round 3: HR interview (fitment, motivation, salary discussion)

Docs.google.com (Google) is known for a collaborative, innovation‑first culture where engineers and analysts are encouraged to experiment and share ideas. Employees enjoy generous learning budgets, clear career ladders and a healthy work‑life balance supported by flexible hours and remote‑work options.

Graduates (B.Tech/B.E., B.Sc., B.Com, M.Tech, M.Sc.) in Computer Science, Information Technology, Statistics, Mathematics, Engineering or related fields; minimum 60% aggregate (or CGPA 6.5/10); final year students of 2025‑2027 batches are eligible; no active backlogs at the time of joining; strong foundation in programming, statistics and data handling.

Credeau is an emerging FinTech startup focused on building data‑driven risk and compliance solutions for the financial services sector. Leveraging cutting‑edge machine learning, natural language processing and advanced analytics, the company helps lenders, insurers and payment platforms make smarter underwriting decisions. With a culture that encourages rapid experimentation, cross‑functional collaboration and continuous learning, Credeau has quickly become a preferred destination for young talent eager to work on real‑world financial datasets. As a Data Analyst / Data Scientist at Credeau, you will be part of a high‑impact team that transforms raw financial, bureau and transactional data into actionable risk insights. You will work closely with risk analysts, product managers and engineering teams to design, prototype and deploy underwriting strategies that balance business growth with credit risk. The role offers exposure to the entire analytics lifecycle – from data extraction and cleaning, through exploratory analysis and model building, to post‑deployment monitoring and optimisation. Key Responsibilities: 1. Design and develop risk‑based underwriting and decision strategies using structured financial data. 2. Extract, clean and transform large datasets with SQL and Python (Pandas, NumPy). 3. Conduct exploratory data analysis to uncover patterns, anomalies and segment‑level behaviours. 4. Build, evaluate and fine‑tune machine‑learning models for credit scoring, fraud detection and recommendation. 5. Design and run A/B experiments or simulations to measure strategy impact on approval rates and risk metrics. 6. Communicate experiment findings and analytical insights to both technical and non‑technical stakeholders. 7. Collaborate with software and data engineers to ensure seamless data pipelines and model deployment. 8. Monitor post‑deployment performance, detect degradation, and recommend corrective actions. 9. Document methodologies, assumptions and experiment designs for audit and compliance purposes. 10. Stay updated with emerging techniques in NLP, statistical modelling and data visualisation to continuously improve product offerings. Tech Stack: Python (Pandas, NumPy, Scikit‑learn), SQL, Jupyter notebooks, Git, Docker, basic cloud services (AWS/GCP), Tableau/PowerBI for visualisation, and familiarity with NLP libraries (spaCy, NLTK). Growth Path: Starting as an Analyst, you can progress to Senior Data Scientist, Lead Risk Analyst, or Product Analytics Manager within 2‑3 years, depending on performance and domain expertise. Credeau encourages certifications, conference participation and internal hackathons to accelerate career growth. Why Join Credeau? You will work on high‑impact financial products that directly influence lending decisions, gain hands‑on experience with end‑to‑end ML pipelines, and be mentored by industry veterans. The fast‑paced environment rewards curiosity, offers competitive compensation and provides a clear roadmap for professional advancement.