Analytic Science Scientist I

FICO's interview process typically starts 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 focuses on cultural fit and motivation. Candidates should be comfortable with Python/Java coding, statistical concepts, and clear communication of 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, making it a balanced place to grow both professionally and personally.

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 & logical reasoning test → Round 2: Technical interview (coding, statistics, case studies) → Round 3: HR interview (fit, motivations, cultural alignment)

FICO (NYSE: FICO) is a global leader in analytics software, serving more than 100 countries with solutions that help businesses make smarter, data‑driven decisions. With a heritage of pioneering credit scoring, the company has expanded into a broad portfolio that includes fraud detection, risk management, and decision‑optimization platforms. In India, FICO operates out of major tech hubs such as Bangalore, where it blends cutting‑edge research with real‑world product delivery, offering a vibrant environment for fresh talent to grow alongside seasoned scientists and engineers. The organization prides itself on an inclusive culture that encourages ownership, customer delight, and mutual respect, making it an attractive destination for ambitious graduates. The Analytic Science Scientist I role is an entry‑level position designed for candidates who are passionate about turning massive data sets into actionable predictive models. As part of a multidisciplinary team, you will be involved in the end‑to‑end lifecycle of model development – from data exploration and feature engineering to algorithm selection, validation, and production deployment. You will also get exposure to client‑facing activities, helping translate technical outcomes into business value, and will collaborate with software, product, and support teams to ensure seamless integration of analytics solutions. 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. The tech stack revolves around Python or Perl for scripting, Java/C++ for integration, and statistical packages such as R or SAS for advanced analysis. Familiarity with machine‑learning libraries (scikit‑learn, TensorFlow, PyTorch) and data‑handling tools (SQL, Hadoop, Spark) is advantageous. The role offers a clear growth path: successful analysts can progress to Senior Scientist, Team Lead, or Product Manager positions, eventually influencing strategic product roadmaps. Why join FICO? You will work on high‑impact projects that influence Fortune‑500 decisions, receive mentorship from industry veterans, and benefit from a culture that rewards curiosity and initiative. The company’s competitive compensation, robust learning programs, and emphasis on work‑life balance make it an ideal launchpad for a career in analytics and data science.