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Open nowFirst seen 37 hours ago

Data Science Manager

Noraa & Co.43 open roles

Where
Jakarta, Jakarta, Indonesia
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Your applicationOpen nowData Science ManagerNoraa & Co. · Jakarta, Jakarta, Indonesia

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  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Noraa & Co.'s own form.

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The clock on this job

Early applications get read.

11.9% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.9%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: first seen 37 hours ago

The posting

About the Opportunity

Our confidential client is a technology-driven organisation operating in a high-urgency, customer-facing environment where reliability, scale, security, and data-informed decision-making are critical.

We are seeking a hands-on Data Science Manager to lead the development of analytical and machine-learning capabilities that support business growth, operational performance, customer experience, and strategic decision-making.

This role requires a leader who can translate complex business problems into practical, measurable data solutions; develop a capable team; and partner closely with Product, Engineering, Operations, Technology, and business stakeholders.

Key Responsibilities

  • Lead, mentor, and develop a high-performing data science and analytics team.
  • Define and execute a practical data science roadmap aligned with business priorities and measurable outcomes.
  • Partner with Product, Engineering, Operations, Technology, and commercial stakeholders to identify high-impact data opportunities.
  • Translate ambiguous business questions into structured analytics, experimentation, forecasting, optimisation, segmentation, predictive-modelling, or machine-learning initiatives.
  • Oversee the end-to-end data science lifecycle: problem framing, data exploration, feature development, model design, validation, deployment, monitoring, and continuous improvement.
  • Establish standards for data quality, experimentation, statistical rigour, model validation, documentation, reproducibility, and responsible use of data.
  • Ensure models and analytical products are reliable, scalable, explainable where appropriate, and fit for production environments.
  • Work with Data Engineering and Software Engineering teams to improve data accessibility, data pipelines, model deployment, and model monitoring.
  • Communicate insights, recommendations, risks, and model performance clearly to senior leaders and non-technical stakeholders.
  • Drive adoption of data-informed decision-making across relevant business and operational functions.
  • Define success metrics for data science initiatives, including business impact, model performance, operational adoption, and return on investment.
  • Contribute to data governance, privacy, security, and model-risk practices.
  • Support team planning, recruitment, capability development, and the continuing maturity of the data science function.

Qualifications and Experience

  • Bachelor’s degree or higher in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, Physics, or another relevant quantitative discipline.
  • Proven experience leading data science, advanced analytics, machine learning, or decision-science initiatives.
  • Demonstrated people-leadership experience, including coaching, developing, and managing data science or analytics professionals.
  • Strong practical understanding of statistical analysis, experimental design, predictive modelling, machine learning, and data storytelling.
  • Strong proficiency in Python and SQL.
  • Experience working with large, complex, and production-relevant data sets.
  • Experience translating business needs into analytical and machine-learning solutions with measurable impact.
  • Experience working with cross-functional stakeholders in a fast-paced technology or operational environment.
  • Strong commercial judgement to prioritise data initiatives based on business value, feasibility, data readiness, risk, and expected impact.
  • Clear communication skills, including explaining technical findings to technical and non-technical stakeholders.
  • Professional English communication skills.

Preferred Qualifications

  • Experience with cloud data and machine-learning platforms such as AWS, Google Cloud, Azure, Databricks, Snowflake, or equivalent environments.
  • Experience with MLOps practices, including model versioning, experiment tracking, CI/CD, monitoring, and model governance.
  • Experience in a large-scale digital, platform, fintech, e-commerce, marketplace, logistics, mobility, or other technology-driven environment.
  • Experience with customer analytics, risk, fraud, personalisation, recommendation, optimisation, operational intelligence, or other data-intensive use cases.

Application Note

Noraa & Co. is supporting this recruitment process on behalf of our confidential client. Shortlisted candidates will be contacted for further discussion.

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