Analytic Science Scientist I

FICO's interview process typically begins with a timed online aptitude test, followed by a technical interview that blends coding challenges, statistical case studies, and discussion of past projects. The final HR round assesses cultural fit and motivation, with interviewers looking for clear communication and analytical thinking.

FICO promotes a people‑first environment where collaboration and continuous learning are encouraged. Employees enjoy flexible work hours, regular knowledge‑sharing sessions, and clear pathways for career advancement, ensuring a balanced professional and personal life.

Bachelor's or Master's degree in Statistics, Engineering, Mathematics, Computer Science, Physics, Operations Research or related field. Minimum 60% aggregate (or CGPA 6.5/10). No active backlogs at the time of joining. Fresh graduates of the 2025 batch are preferred; candidates from earlier batches may apply if they meet the experience criteria.

Round 1: Online Aptitude Test → Round 2: Technical Interview (coding challenges, statistical case studies, project discussion) → Round 3: HR Interview

FICO (Fair Isaac Corporation) is a global leader in analytics software and decision‑management solutions, serving more than 100 countries. Founded in 1956, the company pioneered credit scoring and has since expanded its portfolio to include fraud detection, risk management, and AI‑driven decision optimisation. In India, FICO operates from major technology hubs such as Bangalore, where it blends cutting‑edge research with real‑world product delivery. The organisation is known for its inclusive culture, strong emphasis on continuous learning, and clear career progression pathways for technical talent. The Analytic Science Scientist I role is designed for fresh graduates who are passionate about turning massive data sets into actionable insights. As an entry‑level data scientist, you will work closely with senior scientists, software engineers, and product managers to build, evaluate, and deploy predictive models that drive business outcomes for FICO’s clients. You will be exposed to the full model lifecycle—from data ingestion and cleaning to algorithm selection, validation, and post‑deployment monitoring—providing a solid foundation for a career in advanced analytics. Key responsibilities include: 1. Building and evaluating predictive and decision models using large historical data sets. 2. Performing data cleaning, filtering, and feature creation to prepare data for modeling. 3. Conducting experiments with various algorithms (e.g., regression, SVM, neural networks) and selecting the best performing model. 4. Validating production data and analyzing score distributions post‑deployment. 5. Assisting in client meetings to troubleshoot production data issues and explain model behavior. 6. Applying data‑mining methodologies to investigate model performance and suggest improvements. 7. Managing project timelines and coordinating with cross‑functional teams (software, IT, product management). 8. Documenting model development processes, assumptions, and results for internal and external stakeholders. 9. Participating in post‑implementation support and continuous model monitoring. 10. Staying updated with the latest research in machine learning, statistical methods, and big‑data technologies. Tech stack typically includes Python (pandas, scikit‑learn, TensorFlow/PyTorch), SQL, Hadoop/Spark for big‑data processing, and version‑control tools like Git. Familiarity with Java or Scala is a plus. The role offers a clear growth path: after gaining experience, analysts can progress to Senior Scientist, Lead Scientist, and eventually to managerial or specialist roles in AI research and product strategy. Why join FICO? The company provides a people‑first environment with flexible work hours, regular knowledge‑sharing sessions, and mentorship from industry veterans. Freshers receive hands‑on exposure to real‑world problems, competitive compensation, and a platform to build a strong analytics career in a globally recognised brand.