Senior Data Scientist

Infosys Finacle

Chennai District

On-site

INR 1,800,000 - 3,200,000

Full time

8 hours ago
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Job summary

Infosys Finacle is seeking an experienced Data Scientist / AI Engineer to design, develop, and deploy advanced AI solutions. You will build predictive models, optimize customer experience, and ensure models are production-ready with explainable AI practices.

The role emphasizes collaboration with cross-functional teams, delivering measurable business outcomes, and staying ahead of AI trends in a fast-paced environment.

Qualifications

  • Strong analytical and problem-solving skills with a data-driven mindset.
  • Proficiency in Python and SQL (statistical or ML libraries).
  • Experience with large and complex datasets.
  • Advanced statistical concepts and ML algorithms.

Responsibilities

  • Design, develop, and deploy advanced AI and ML solutions to solve complex business problems.
  • Build predictive models to optimize customer experience and revenue growth.
  • Host ML models as API-ready services for integration.
  • Promote Explainable AI and Responsible AI practices.

Skills

Python
SQL
ML Algorithms
Production APIs
Explainable AI
Communication
Problem Solving

Job description

Job Title: Data Scientist and Senior Data Scientist / AI & Machine Learning Engineer

Experience Required

Minimum 8+ years of relevant experience in Data Science, Machine Learning, or Artificial Intelligence.

Job Summary

We are seeking an experienced and highly motivated Senior Data Scientist / AI Engineer to work on cutting‑edge AI solutions in collaboration with leading business partners. The ideal candidate will design, build, deploy, and explain advanced machine learning models that drive measurable business outcomes while adhering to principles of Explainable and Responsible AI.

Key Responsibilities
  • Design, develop, and deploy advanced AI and Machine Learning solutions to solve complex business problems.
  • Build predictive and prescriptive models to optimize customer experience, revenue growth, ad targeting, and other key business metrics.
  • Host machine learning models and make them API‑ready for integration with applications and platforms.
  • Apply predictive modeling, simulation, scenario analysis, and clustering techniques to generate actionable insights.
  • Design and run experiments, prototypes, proofs of concept (PoCs), and MVPs.
  • Promote and implement Explainable AI (XAI) and Responsible AI practices.
  • Partner closely with cross‑functional teams to translate business requirements into scalable AI solutions.
  • Identify opportunities to reuse datasets, models, and insights across different functions within the organization.
  • Communicate findings clearly and effectively to technical and non‑technical stakeholders.
  • Stay current with emerging AI/ML trends and continuously experiment with new approaches.
  • Embrace a fast‑paced, innovation‑driven culture: Move fast, learn continuously, and make an impact.
Required Skills & Qualifications
  • Strong analytical and problem‑solving skills with a data‑driven mindset.
  • Proficiency in Python and SQL (experience with statistical or ML libraries is expected).
  • Experience working with large and complex datasets.
  • Strong knowledge of advanced statistical concepts, including:
  • Statistical distributions
  • Hypothesis testing and proper statistical usage
  • Hands‑on experience with machine learning and AI algorithms, including:
  • Supervised and unsupervised learning
  • Decision trees and ensemble methods
  • Neural networks and deep learning
  • Experience deploying models and converting them into production‑ready APIs.
  • Strong communication and presentation skills, with the ability to explain complex concepts to non‑technical audiences.
Preferred Qualifications
  • Experience working in fast‑paced, agile, or research‑driven environments
  • Exposure to cloud platforms and MLOps practices
  • Passion for innovation, experimentation, and continuous learning
Preferred Skills

Must be into pure Data science

Note: Not considering Data engineering and Data analytics profile.
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