- Role: Data Science
- Location: Mumbai, Gurugram, Bengaluru
- Company: PWC
- Salary: Not Disclosed
- Qualifications: Any Graduate or Postgraduate
- Experience: 2 – 7 years
- Employment Type: Full Time, Permanent
Job Description:
The Data Science role at PwC includes growing predictive models and analytical gear to come across and save you from financial crimes. Responsibilities consist of studying complicated datasets to identify suspicious sports, participating with go-purposeful groups to lay out innovative answers, and staying current on evolving industry guidelines. The position additionally requires presenting insights to senior stakeholders to influence decision-making. Ideal candidates must have 2-7 years of experience in information technological know-how, focusing on monetary crimes compliance (FCC) and information in AML/KYC techniques.
Key obligations include:
- Predictive Model Development: Leading the improvement of fashions that leverage huge facts to predict ability economic crimes. This entails managing large, complex datasets and applying records science techniques together with device mastering, herbal language processing (NLP), and statistical modeling to extract insights.
- Data Analysis for Anomaly Detection: Analyzing datasets to find hidden patterns, trends, or anomalies that can imply suspicious sports. This information-driven approach enables toughened financial crime detection strategies, enabling corporations to live a step ahead of fraudulent sports.
- Collaboration with Cross-Functional Teams: Data scientists at PwC collaborate with distinct departments, inclusive of criminal, compliance, and technology, to design innovative answers for monetary crime prevention. These teams work collectively to expand new tactics, combine regulatory necessities, and improve existing structures for a higher compliance framework.
- Staying Updated on Industry Regulations: Financial crime is a closely regulated vicinity, and the function needs to stay up to date on modern-day policies and industry excellent practices. This ensures that PwC’s solutions and analytical fashions observe evolving policies and make contributions to more powerful regulatory compliance.
- Stakeholder Communication: Presenting statistics-driven insights and findings to senior stakeholders is an essential part of the function. Data scientists want to articulate their results and pointers in reality, helping shape strategic choices that impact the organization’s compliance and chance management techniques.
Key abilities include:
- AML/KYC Compliance: Experience with anti-money laundering (AML) and knowing your customer (KYC) policies is important, as these are fundamental to financial crime prevention.
- Tools and Platforms: Familiarity with gear which includes JIRA, Jocata, FIS, Amlock, Actimize, and Compass is favored. These systems are regularly used for regulatory compliance, risk management, and workflow management in financial crime prevention.
- Technical Proficiency: The capacity to paint with huge datasets using programming languages such as Python, R, or SQL is essential. Data scientists ought to also be proficient in gadgets gaining knowledge of frameworks like TensorFlow, Scikit-examine, or PyTorch to build predictive fashions.
- Communication and Presentation Skills: The ability to translate complex records insights into actionable hints for commercial enterprise stakeholders is an essential part of this role. Strong communique and presentation competencies will help have an effect on decision-making in the senior stage.
Education and Experience Requirements:
Educational Background:
A diploma in Data Science or a related field is required.
A postgraduate qualification is desired however no longer mandatory if the candidate has robust relevant experience.
Relevant Experience:
2 to 7 years of experience in a comparable function is important.
Prior experience in facts and technological know-how roles specializing in regulatory compliance and risk control is fantastically proper.
Industry-Specific Experience:
Experience within the monetary offerings area is desired, specifically with expertise in economic crimes compliance (FCC)
Technical Expertise:
- Strong technical competencies in facts evaluation, system learning, and predictive modeling.
Proficiency with gear used in monetary crime prevention and compliance (e.g., JIRA, Actimize, Amlock).
Key Skills: - Familiarity with AML/KYC rules and information on enterprise gear for detecting and preventing financial crimes.
Flexibility in Educational Requirements:
Graduates with robust arms-on experience in statistics technology and analytics may also be considered even though they lack a postgraduate qualification.
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