Data Scientist at Techcombank
Confirmed open
Develop machine-learning models and actionable business insights for Techcombank in Ho Chi Minh City.
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Role overview
This Techcombank data-science role analyzes large structured and unstructured datasets to support business objectives and customer experiences. The work spans modeling, insight generation and model monitoring.
Responsibilities
- Build machine-learning and deep-learning solutions, including recommendation engines, predictive models and customer-journey analytics.
- Mine bank data, identify trends and explain insights that inform business strategies.
- Monitor model performance and data accuracy; evaluate new data sources and gathering methods.
- Work with business squads to frame analysis questions and deliver projects using agile methods and internal controls.
Qualifications
- Bachelor’s degree in statistics, mathematics, quantitative analysis, computer science, software engineering or IT.
- At least five years of relevant work with data analysis, machine learning or deep learning and deployment of statistical models.
- Ability to query databases and program with tools such as Python, R, SQL, Scala, Java or Tableau.
- Experience explaining complex analysis, optimization methods and work in agile teams; English per Techcombank policy.
Technology in this role
- Python: Ability to query databases and program with tools such as Python, R, SQL, Scala, Java or .
- Java: Ability to query databases and program with tools such as Python, R, SQL, Scala, Java or .
- C++: C, C++, R, Python, Scala, SQL, Java, Tableau, .
- SQL: Ability to query databases and program with tools such as Python, R, SQL, Scala, Java or .
- C: C, C++, R, Python, Scala, SQL, Java, Tableau, .
- Scala: Ability to query databases and program with tools such as Python, R, SQL, Scala, Java or .
- R: Ability to query databases and program with tools such as Python, R, SQL, Scala, Java or .
Role-specific candidate guide
Preparation notes based on the employer’s stated responsibilities and qualifications.
Understanding the scope. This Data Scientist (40000032) position at Techcombank is best assessed through the work described in the employer’s posting, rather than the title alone. The available role overview says: “This Techcombank data-science role analyzes large structured and unstructured datasets to support business objectives and customer experiences. The work spans modeling, insight generation and model monitoring.” Read that statement together with the responsibilities below to understand the likely balance between delivery, coordination and technical decision-making. The role belongs to the AI and data area, but that label is only a guide to the work; the employer’s own requirements remain decisive. Before applying, check the original listing for reporting lines, product or team assignment, employment terms and any details that may have changed since this copy was checked. Where this page says a fact is not specified, treat it as an open question rather than an implied promise.
What the responsibilities signal. The posting specifically names “Build machine-learning and deep-learning solutions, including recommendation engines, predictive models and customer-journey analytics.”; “Mine bank data, identify trends and explain insights that inform business strategies.”; “Monitor model performance and data accuracy; evaluate new data sources and gathering methods.”. For each duty, identify a project where you performed comparable work and be ready to describe the context, your own contribution, constraints, decisions, and measurable result. Explain how you moved from the initial need to implementation, review, release or operational follow-through, where those stages apply. If the work involved other teams or users, distinguish your decisions from the group’s contribution. Avoid presenting a technology keyword as proof by itself: connect it to the problem you solved, the scale or complexity involved, and what changed after your work. The source may contain additional duties; review it directly before preparing your application.
How to read the requirements. The listed qualifications include “Bachelor’s degree in statistics, mathematics, quantitative analysis, computer science, software engineering or IT.”; “At least five years of relevant work with data analysis, machine learning or deep learning and deployment of statistical models.”; “Ability to query databases and program with tools such as Python, R, SQL, Scala, Java or Tableau.”. Mark each requirement as demonstrated, adjacent experience or a genuine gap, then use a concise example for the first two categories. A strong example explains what you personally owned, how you made trade-offs, how you validated the result and what you learned. If the posting specifies years of experience, language ability, certifications, location or eligibility, address those facts plainly in your CV or application rather than relying on the employer to infer them. Do not claim a qualification from exposure alone. For a requirement you do not meet, describe relevant transferable experience accurately and ask the recruiter whether it is mandatory.
Technology and working evidence. The technology terms associated with this listing are Python, Java, C++, SQL. Treat this as a set of posting-derived signals, not a guarantee that every tool is used daily or that the list is complete. For each term relevant to your experience, prepare one concrete example: the system or workflow, the part you owned, the alternatives considered, and how you tested reliability, security, performance or usability as appropriate. If you have not used a named tool, explain the closest related system you have worked with and how you would ramp up; do not relabel that experience as direct production use.
About Techcombank
Techcombank describes this position within its data and analytics work. The official posting does not specify a work arrangement or role-specific benefits.
Employer websiteHow to apply
Review the original posting and apply through the employer’s careers page.
View source and applySource checked: 2026-10-11
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