Pre-sales & Analytics Consultant

Crifasia; Philippines; On-site; PHP 1,200,000 - 1,800,000; Full time

Job summary

A leading analytics and consulting firm in the Philippines is seeking a professional who will bridge the gap between sales and the technical team. The role involves understanding customer needs, proposing appropriate solutions, and managing project delivery. The ideal candidate will hold a degree in a relevant field, have at least 6 years of experience in credit risk management, and possess strong analytical and communication skills. Proficiency in tools like Excel and PowerPoint is essential, along with knowledge in predictive analytics.

Qualifications

• Minimum 6 years’ experience with a prominent bank or consulting firm of developing predictive models in credit risk management.
• Experience in pre-sales or project delivery management of scoring and regulatory solutions in the credit risk domain.

Responsibilities

• Analyzing customer requirements from RFP/discussions.
• Creating envisioned analytics/consulting solutions to address client needs.
• Building and maintaining strong client relationships.

Skills

Strong analytics and problem-solving skills

Strong written and verbal English communication skills

Good understanding of lending business practices

Experience in predictive analytics techniques

Proficiency in Excel

Proficiency in PowerPoint

Education

Bachelor’s degree in Statistics/Mathematics/Data Science/Economics/Banking

Master or MBA

Tools

Python

R

Job description

The role involves bridging the gap between sales and the technical team, focusing on understanding customer needs and aligning CRIF’s analytics and consulting offerings to meet those requirements. This role requires a blend of technical knowledge, analytical skills, and strong communication to effectively demonstrate how CRIF’s solutions can solve customer problems in the Philippines.

KEY RESPONSIBILITIES

• Understanding Customer Needs: Analyzing customer requirements from RFP/discussions and understanding their business goals and challenges.
• Propose Appropriate Solution: Basis the prospective client’s requirements, create an envisioned analytics/consulting solution (in PowerPoint presentation) to address the client and present the solution to client’s key decision makers.
• Address Client Clarifications: Answer the technical and business questions about the proposed solution and its potential improvements in the current practices.
• Proposal Creation: Create a detailed proposal defining the scope, estimated effort/price and timeline to deliver the solution.
• Delivery Management
  • Create a project plan and form a delivery team
  • Provide key data requirements to the client
  • Assess data quality and sufficiency
  • Collaborate with internal and external stakeholders
  • Ensure adherence to project budget and timelines
  • Present intermediate and final deliverables
• Building Relationships: Establishing and maintaining strong relationships with clients to foster trust and collaboration to find cross-sell / up-sell opportunities from existing client.

ABOUT YOU

MINIMUM QUALIFICATION/SKILLS

• Bachelor’s degree in Statistics/Mathematics/Data Science/Economics/Banking (Master or MBA considered a plus)
• Minimum 6 years’ experience with a prominent bank or consulting firm of developing predictive models in the credit risk management domain
• Strong analytics and problem-solving skills
• Strong written and verbal English communication skills
• Good understanding of lending business practices and data leveraged throughout the lifecycle of the credit
• Experience in predictive analytics techniques (regression and machine learning) especially in the credit risk domain
• Good knowledge of the type of scorecards used in origination, customer management, collections and regulatory practices
• Experience in pre-sales or project delivery management of scoring and regulatory solutions in the credit risk domain
• Proficiency in Excel and PowerPoint skills

GOOD TO HAVE

• Knowledge of the most common data processing/modelling tools (Python/R or any relevant programming language)
• Knowledge of credit bureau data and its use in lending practices
• Prior experience of process consulting and pre-sales in the credit risk domain
• Experience in regulatory compliance especially Expected Credit Loss (ECL) modeling complying IFRS9/PFRS9 guidelines
• Knowledge of financial statements and ratio analysis