Data Scientist

PT Sepulsa Teknologi Indonesia (Jakarta); Jakarta Utara; On-site; IDR 334,800,000 - 613,800,000; Full time

Job summary

PT Sepulsa Teknologi Indonesia (Jakarta) is seeking a proactive Data Scientist to join our Alternative Credit Scoring team. You will build predictive models, explore new data opportunities, and develop analytics solutions for the financial industry.

Beyond modeling, you will promote data-driven thinking, educate stakeholders, and help teams understand how DS can solve business problems. This role suits someone who enjoys building from scratch, learning independently, and taking ownership in a

Qualifications

• Bachelor's degree or higher in a quantitative field.
• Strong foundation in statistics, ML, and feature engineering.
• Proficiency in Python, SQL, and ML libraries.

Responsibilities

• Analyze large-scale datasets to generate insights and build predictive models.
• Improve existing credit scoring models through feature engineering and evaluation.
• Research new data products, AI/ML solutions, and analytics approaches.
• Translate business problems into data-driven solutions and identify data opportunities.
• Collaborate with Product, Engineering, and Commercial teams to deliver scalable data solutions.
• Validate model performance and communicate findings to diverse stakeholders.
• Promote data-driven decision making and raise DS awareness across the organization.
• Maintain documentation for models, features, and analytics processes.
• Stay updated with trends in DS, AI, and ML.

Skills

Python

SQL

Jupyter Notebook

Git/GitHub

Pandas

NumPy

Scikit-learn

XGBoost

LightGBM

Data storytelling

Education

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related field

Tools

BigQuery

AWS

Git

Job description

We are looking for a proactive, curious, and business-oriented Data Scientist to join our Alternative Credit Scoring team. As one of the first Data Science members in the company, you will play a key role in improving our existing scoring products, exploring new data opportunities, and developing innovative analytics solutions for the financial industry.

Beyond building models, you will act as a Data Science advocate by promoting data-driven thinking, educating stakeholders, and helping cross-functional teams understand how Data Science can solve business problems. This role is ideal for someone who enjoys building from scratch, learning independently, and taking ownership in a fast-growing environment.

Responsibilities

Analyze large-scale datasets to generate insights and develop predictive models.

Enhance and continuously improve existing alternative credit scoring models through feature engineering, experimentation, and model evaluation.

Research and propose new data products, AI/ML solutions, and analytical approaches.

Translate business problems into data-driven solutions and proactively identify opportunities to create new data products.

Collaborate closely with Product, Engineering, and Commercial teams to deliver scalable data solutions.

Validate and monitor model performance, and communicate analytical findings to both technical and non-technical stakeholders.

Act as a Data Science advocate by promoting data-driven decision making, educating stakeholders, and increasing Data Science awareness across the organization.

Develop and maintain documentation for models, features, and analytical processes.

Stay up to date with the latest trends and best practices in Data Science, AI, and Machine Learning.

Requirements

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related field.

2+ years of experience in Data Science, Machine Learning, Risk Analytics, or related fields.

Strong understanding of statistics, predictive modeling, machine learning, and feature engineering.

Proficient in Python, SQL, Jupyter Notebook, and Git/GitHub.

Experience with Pandas, NumPy, Scikit-learn, XGBoost, LightGBM, or similar machine learning libraries.

Familiar with cloud data platforms such as Google BigQuery, AWS, or equivalent.

Experience evaluating classification models using metrics such as AUC, KS, Gini, Precision/Recall, PSI, and model stability is a plus.

Experience working with alternative data, fintech, banking, financial services, or credit scoring is highly preferred.

Experience translating business problems into analytical solutions and proactively identifying opportunities to create new data products.

Strong communication and presentation skills, with the ability to explain technical concepts to non-technical audiences.

Passionate about promoting data literacy and advocating the adoption of Data Science and AI across the organization.

Self-driven, proactive, highly curious, and able to learn independently with minimal supervision.

Strong ownership mindset and comfortable working in a fast-paced startup environment.