Senior Data Scientist
At a glance
Senior Data Science role at Fa Ewjt Saasfaprod1. Gurugram · full-time.
Pay not stated Data Scientist salary
dataroles summary, based on the employer's posting.
What you'll do
- Take analysis from business goals through data exploration, then turn findings into practical actions
- Build and deploy scalable machine learning solutions for transaction monitoring and risk scores, improving alerts and investigations
- Retune statistical and machine learning models on large datasets to improve performance, efficiency and robustness
- Test model results with suitable metrics, then validate models with the Model Risk Management team across business entities
- Document model design and methods, review reports, and share recommendations with business and technology stakeholders
What you bring
- A degree in engineering, economics, statistics, mathematics or another related technical field
- At least eight years in data science, analysis, reporting, research or another listed discipline
- At least eight years developing and implementing machine learning models with SAS, SQL, Python or another listed tool
- Working knowledge of compliance risks, especially transaction monitoring, screening and client due diligence
Who this fits
This senior individual-contributor role suits someone who can work directly with business partners to clarify problems and communicate findings to technical and business audiences. You’ll need to work a flexible schedule across time zones. The role is based in Gurugram, India, with a hybrid arrangement.
From the employer
NA
Essential Functions:
- Strong analytical skills and compliance domain knowledge, with the ability to conduct large scale data analysis through all stages: understand business goal and strategy, formulate analytic approaches, perform data extraction and exploration, and translate results into actionable items
- Expertise in advanced techniques (Machine learning, natural language processing, deep learning), including exposure to Generative AI technologies and their applications. Experience with Python libraries such as pandas, numpy, matplot and Scikit
- Deployment of high-performance scalable AI/machine learning (ML) algorithms for building transaction monitoring and risk scoring solutions to improve the quality of alerts and investigation process
- Conduct periodic tuning of statistical and machine learning models using large-scale datasets to optimize models for performance, efficiency, and robustness
- Well versed with Compliance risk typologies and rules. Good knowledge and deployment experience of rules and typologies
- Design and conduct experiments to evaluate the model performance using appropriate metrics and statistical analysis to measure and interpret results
- Supervise and work with the Model Risk Management team as an independent contributor to support model validations across multiple business entities. Ensure the accuracy, reliability, and compliance of models by overseeing and conducting thorough validations
- Collaborate with internal stakeholders across business units and regulated entities to enhance alignment in implementing MRM policy/standards and promote MRM best practices
Prepare technical documentation, including model architecture, implementation details and model methodology. Review model reports and communicate findings, insights, and recommendations to both technology and business stakeholders
Qualifications
Basic Qualifications:
∙ Bachelor's/Master’s Degree in Engineering, Economics, Statistics, Mathematics, or related technical discipline
∙ At least 8 years of experience in data science, analysis, reporting, statistical analysis, research, data mining, trend analysis etc.
∙ At least 8 years of experience in machine learning model development and implementation using tools like SAS, SQL, Python/R , Hive and/or Spark
∙ Building predictive and descriptive statistical models using AI/ML algorithms (e.g., logistic regression, random forests, SVMs, XGBoost, CNNs/RNNs)
∙ Compliance domain knowledge primarily for transaction monitoring, screening and client due diligence
∙ Excellent knowledge of database management, data extraction and data manipulation skills
∙ Superior communication, business writing and stakeholder management skills
∙ Self-motivated and proactive in talking to business partners/clients to identify and understand problem statements
∙ Passionate about building end-user experiences that deliver measurable value without increasing complexity
∙ Willing to work on a flexible schedule across different time zones
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