FIS Global

Data Scientist

FIS Global
3.5 / 5
Pune Not disclosed
Yesterday
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About the job

Position Type : Full time Type Of Hire : Experienced (relevant combo of work and education) Education Desired : Bachelor of Computer Engineering Data Scientist About the role: Data Scientist required to lead funded (billable) projects, customizing and implementing Forecasting, Anomaly detection, Classification and GPT-like solutions (generative AI, (R)etrieval/ (A)ugmentation/ (G)eneration architecture for automated prompt-engineering, etc.) for client-facing systems in Capital Markets. What you will be doing: • Use quantitative and statistical methods to extract data and insights from structured and unstructured data. Leverage machine learning, statistical modeling, and quantitative analysis to create smarter, data-driven products. • The candidate should understand both ML and Gen AI. • Employ machine learning and statistical modeling to create and enhance data driven products • Analyze and extract insights from internal and external data • Work with Big Data and transform complex datasets into more usable formats • Work with a variety of data science tools and programming languages such as SAS, Python, R, Scala, SQL • Work independently and collaborate with other groups to solve complex problems • Create and present analyses to internal and external partners and clients • Document models and write code to track and monitor models and product performance • Understand the realities of model development and make pragmatic and business-aware choices when trading-off sophistication and accuracy versus implementation and performance costs. • Other related duties assigned as needed EDUCATION REQUIREMENTS- Bachelor degree with relevant experience (Minimum 3 years) but Masters or PhD is preferred in Statistics, Decision Sciences, Applied Mathematics, Economics or Computer Science or the equivalent combination of education, training, and work experience. • Delivery-oriented team player who takes responsibility for the team’s success and strives to continually learn and improve. • Ability to interface with all levels of employees and effectively interact with various functional areas and facilities. • Ability to establish and maintain effective working relationships with employees, management, and clients. What you will need: • 6+ Years of relevant experience and knowledge in machine learning, artificial intelligence, statistical modeling, data visualization, and data analysis. • Proficient in data science tools and programming languages such as SAS, Python, R, Scala, SQL • Experience or knowledge of cloud-based technology along with Azure and Databricks proficiency. • Knowledge of financial services industry especially Capital Markets. • Deep understanding of Fraud/Anomaly detection use cases and approach – Models like Auto encoder, XG Boost, Isolation Forest, Local Outlier factor, SVMs etc. • Deep understanding on RAG, MCP & Agentic AI deployments. • Outstanding verbal and written communication skills to technical and non-technical audiences of various levels in the organization, e.g., executive, management, individual contributors • Excellent analytical, decision-making, problem-solving, team, and time management skills • Ability to persuade and influence others on the best approach • Positive outlook, strong work ethic, and responsive to internal and external clients and contacts • Ability to work as part of a team or alone making a strong contribution in either scenario • Exceptional statistical, mathematical, basic Machine learning and analytical skills • Superior interpersonal, communication and presentation skills.

Requirements

  • machine learning
  • data analysis
  • statistics
  • generative AI
  • data visualization

Qualifications

  • Bachelor's degree in Computer Engineering
  • Master's or PhD in Statistics, Decision Sciences, Applied Mathematics, Economics or Computer Science

Preferred Technologies

  • machine learning
  • data analysis
  • statistics
  • generative AI
  • data visualization

Benefits

  • competitive salary
  • collaborative work environment
  • opportunities to give back
  • always-on learning and development

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