We are seeking passionate and self-driven Data Scientists with strong expertise in Machine Learning (ML) and MLOps to join our team. This role is ideal for individuals who are intellectually curious, technology-driven, and passionate about solving real-world business challenges. As a Data Scientist, you will apply advanced analytics and machine learning techniques to deliver actionable insights and optimize business outcomes in domains such as financial services, banking, and risk compliance.

Key Responsibilities

1. Machine Learning and Model Development. Design, implement, and deploy machine learning models to address business problems. Work on end-to-end model development lifecycle, including data preprocessing, model training, and evaluation.
2. MLOps. Collaborate with cross-functional teams to implement best practices for ModelOps, ensuring efficient deployment, monitoring, and management of machine learning models in production.
3. Data Analysis and Insights. Analyze complex datasets to identify trends, patterns, and insights that drive strategic business decisions. Use statistical analysis, machine learning algorithms, and data visualization to communicate findings to business stakeholders.
4. Collaboration with Stakeholders. Work closely with business leaders, data engineers, and other technical teams to understand business needs and deliver machine learning solutions that align with the company's goals.
5. Innovation and Research. Stay updated with the latest advancements in machine learning, AI, and data science. Implement cutting-edge techniques and tools to improve the quality and efficiency of machine learning models.
6. Risk and Compliance. Develop and deploy models in the banking, capital markets, and risk and compliance sectors to optimize operations, improve decision-making, and ensure compliance with industry regulations.

Skills and Experience Required

• Master's degree in Computer Science, Engineering, or related fields.
• Relevant experience in MLOps, cloud technologies, and working within financial services domains (Capital Markets, Banking, Risk and Compliance).

Technical Skills

• Strong experience with Machine Learning algorithms, statistical modeling, and data mining techniques.
• Proficient in programming languages such as Python, R, or Java for implementing machine learning models.
• Experience with cloud platforms (AWS, Azure, GCP) and tools like Docker, Kubernetes, and Terraform for model deployment and scaling.
• Knowledge of MLOps tools like MLflow, Kubeflow, and version control systems like Git.

Domain Expertise

• Strong background in Financial Services or relevant experience in banking, capital markets, and risk & compliance.
• Understanding of business concepts such as risk management, compliance frameworks, and data governance in financial institutions.

Soft Skills

• Excellent communication and interpersonal skills, capable of explaining complex technical concepts to non-technical stakeholders.
• Problem-solving mindset and a passion for innovation.
• Ability to work collaboratively in a fast-paced, cross-functional environment.

Why Infosys?

1. Innovative Projects. Work on cutting-edge technologies and innovative solutions that drive change in industries like financial services, banking, and risk management.
2. Global Exposure. Collaborate with teams across the world and gain exposure to global markets.
3. Learning & Growth. Leverage continuous learning opportunities and access to the latest tools and technologies to enhance your professional development.
4. Inclusive Culture. Be part of a diverse and inclusive environment where your ideas are valued, and creativity is encouraged.

How to Apply. If you are ready to take your career to the next level and have the skills and experience to excel in this role, we encourage you to apply directly or reach out to Anshul Rajput, Systems Engineer at Infosys, for further insights.