Data Analytics Manager

Talent Hunts Indonesia; Daerah Khusus Ibukota Jakarta; On-site; IDR 100.000.000 - 200.000.000; Full time

Job summary

A leading company in the financial industry is seeking an expert in predictive analytics to develop models for credit risk and fraud detection. The ideal candidate will possess extensive experience in machine learning, strong leadership skills, and the ability to communicate effectively with stakeholders. This role involves both technical and strategic responsibilities, making a significant impact on business decisions.

Qualifications

• At least 4 years in ML collection risk or credit scoring models.
• 2 years in leadership roles.
• Strong grasp of machine learning concepts.

Responsibilities

• Manage the end-to-end lifecycle of predictive models.
• Engineer features from data for customer profiling.
• Conceptualize analytic frameworks for business problems.

Skills

Communication

Leadership

Mathematics

Statistics

Machine Learning

Education

Bachelor's degree in quantitative field

Job description

i. Build predictive models for credit risk, collections, fraud, and other business needs in Financial Industry

ii. Manage and own the entire end-to-end lifecycle of buildings and validate predictive models along with their deployment and maintenance

iii. Engineer predictive features from existing data to build refined customer profiles. Identify external data assets to bring into the model mix

iv. Work backwards to conceptualize and design analytic model frameworks to solve business problems

v. Strong communication skills to share your learnings, lead with the given strategy, get multiple stakeholders to buy into the vision and execution of the analytics roadmap

c. Requirements

i. Bachelor's degree or equivalent experience in quantitative field (Statistics, Mathematics, Computer Science, Engineering, etc.)

ii. At least 4 years of hands-on experience in building, evaluating, and monitoring ML collection risk or consumer credit scoring models for financial products

iii. At least 2 years of leadership experience

iv. Solid understanding of mathematics and statistics

v. Sound knowledge of machine learning concepts such as Bagging, Boosting, Recommendation Engines, etc

vi. Expert in feature creation on a variety of data types

vii. Professional experience in building machine learning analytics model development

viii. Understanding of trade-offs between model performance and business needs

ix. Proven experience to formulate data science solutions to business problems

x. Proven ability to communicate with business and know business needs

xi. Work experience and knowledge of more than one domain is a plus - Risk Analytics, Marketing Analytics, Fraud analytics etc.