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Sr. Data Scientist

Devoteam

Jakarta Selatan

On-site

IDR 832.085.000 - 1.164.920.000

Full time

Today
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Job summary

A leading consulting firm in Jakarta Selatan is seeking an experienced Data Scientist to design and deploy advanced analytical models for the banking domain. This role requires a minimum of 10 years of experience, with a significant focus on data analysis and machine learning. Candidates should be proficient in Python or R and familiar with SQL, along with strong communication skills. This position offers the opportunity to innovate in a fast-paced environment while collaborating closely with various stakeholders.

Qualifications

  • Minimum of 10 years of professional experience as a Data Scientist.
  • Significant focus on the banking or financial services industry.
  • Proven experience in building and deploying models for credit risk.

Responsibilities

  • Design and build advanced propensity models and credit risk models.
  • Conduct in-depth analysis of complex datasets.
  • Develop analytical solutions for banking operations.

Skills

Python
R
SQL
Data analysis
Machine learning algorithms
Dashboard building

Tools

Pandas
NumPy
Scikit-learn
Job description
Company Description

Devoteam is a leading consulting firm focused on digital strategy, tech platforms, and cybersecurity.

By combining creativity, tech, and data insights, we empower our customers to transform their business and unlock the future.

With 25 years’ of experience and 8,000 employees across Europe and the Middle East, Devoteam promotes responsible tech for people and works to create better change.

#Creative Tech for Better Change

Devoteam has launched in January 2021 its new strategic plan, Infinite 2024, with the ambition to become the #1 EMEA partner of the leading Cloud-based platform companies (AWS, Google Cloud, Microsoft, Salesforce, ServiceNow), further reinforced by deep expertise in digital strategy, cybersecurity, and data.

Job Description
Key Responsibilities:
  • Model Development: Design, build, and deploy advanced propensity models, credit risk models, and other statistical models to address various business challenges within the banking domain.
  • Data Analysis: Conduct in-depth analysis of large and complex datasets to identify trends, patterns, and anomalies.
  • Analytical Solution: Develop and implement analytical solutions for banking operations, including customer segmentation, fraud detection, and performance optimization.
  • Collaboration: Work closely with business stakeholders, data engineers, and other teams to understand business requirements and deliver effective data-driven solutions.
  • Reporting: Present findings and model performance to both technical and non-technical audiences in a clear and concise manner.
  • Innovation: Stay updated with the latest advancements in data science, machine learning, and the banking industry to propose and implement innovative solutions.
Qualifications

Experience: Minimum of 10 years of professional experience as a Data Scientist, with a significant focus on the banking or financial services industry.

Technical Skills:

  • Good understanding on building performance dashboards, sales models (propensity, segmentation, income proxy), credit models (A-score, B-score)
  • Proficiency in programming languages such as Python or R.
  • Strong knowledge of machine learning algorithms (e.g., classification, regression, clustering).
  • Experience with SQL and database management.
  • Hands‑on experience with data manipulation and analysis libraries (e.g., Pandas, NumPy, Scikit‑learn).
  • Familiarity with big data & cloud technologies is a plus.

Industry Knowledge: Proven experience in building and deploying models for credit risk, propensity modeling, or other relevant banking analytics projects.

Soft Skills:

  • Excellent problem‑solving and analytical skills.
  • Strong communication and presentation abilities.
  • Ability to work independently and as part of a team in a fast‑paced environment.
Additional Information

This position will be assigned to an FSI client's project.

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