Data Analytics Manager

Talent HuntPH; Jakarta Pusat; On-site; IDR 350,000,000 - 600,000,000; Full time

Job summary

Talent HuntPH seeks a senior Data Scientist to build credit risk, collections, and fraud models for the financial sector. You will own the full model lifecycle, engineer features from diverse data, and design analytic frameworks to tackle business problems.

You will lead with strong communication, align analytics with strategy, and drive roadmap adoption across multiple stakeholders in a fast-paced environment.

Qualifications

• Bachelor's degree or equivalent in a quantitative field (Statistics, Mathematics, CS, Engineering)
• 4+ years hands-on experience building, evaluating, and monitoring ML collection risk or consumer credit scoring models for financial products
• 2+ years leadership experience
• Solid understanding of mathematics and statistics
• Knowledge of ML concepts such as Bagging, Boosting, Recommendation Engines, etc
• Expert in feature creation on diverse data types
• Experience in building ML analytics model development
• Understanding trade-offs between model performance and business needs
• Proven ability to formulate data science solutions to business problems
• Proven ability to communicate with business and align with needs
• Experience across multiple domains such as Risk, Marketing, Fraud analytics is a plus

Responsibilities

• Build predictive models for credit risk, collections, fraud, and other business needs in Financial Industry
• Own end-to-end lifecycle of models including deployment and maintenance
• Engineer predictive features to refine customer profiles from existing data
• Conceptualize and design analytic model frameworks to solve business problems
• Communicate learnings and lead analytics roadmap with stakeholders

Skills

Statistics

Machine Learning

Leadership

Communication

Feature engineering

ML model deployment

Risk analytics

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.