[EAF] Senior Data Science & Analytics

The Senior Engineer - Data Science & Analytics is responsible for developing and implementing data-driven solutions to address complex business and technical requirements. This role involves analyzing large datasets, building predictive models, and creating visualizations to generate actionable insights for stakeholders across the organization.

Main Roles and Responsibilities

• Develop statistical models and machine learning algorithms to identify trends, patterns, and correlations in large-scale datasets as per communication and alignment with customer or customer interface.
• Design and build data visualizations, dashboards, and reports to communicate analytical findings to technical and non-technical stakeholders.
• Perform exploratory data analysis and feature engineering to prepare and enrich datasets for modelling and analysis
• Apply advanced statistical techniques to solve classification, regression, and clustering problems.
• Utilize programming languages and data manipulation libraries to clean, transform, and analyze data efficiently.
• Validate model performance and ensure the reliability and accuracy of analytical solutions through rigorous testing and evaluation methodologies.
• Contribute to technical design reviews by providing data-driven perspectives and collaborating with team members on solution improvements.
• Support team members by sharing knowledge of data science techniques, troubleshooting complex analytical problems, and participating in peer code reviews.
• Ensure compliance with applicable industry standards, regulatory requirements, company policies, and quality frameworks applicable to the role and assigned projects.
• Perform other tasks as assigned by Managers.

Job Requirements

• At least 3–4 years of experience.
• Proven professional experience in data science or analytics, with demonstrated experience in building and deploying machine learning models.
• Proven experience with modern data science frameworks and libraries (e.g., Scikit-learn, Pandas, TensorFlow, PyTorch) is required.
• Experience with Data Warehouse (Vault Design).
• Ability to implement solutions from scratch and build products across the full product lifecycle based on the following requirements:
  • Data Science & Statistical Modeling: Statistical Inference, Machine Learning, Model Validation & Evaluation, NLP
  • Data Engineering & Data Pipeline: Data Management, Data Modelling & Design, Python, R
  • ML Deployment & MLOps: Machine Learning Model Deployment, MLOps / ML Lifecycle Management
  • AI / Deep Learning Technologies: PyTorch, Keras, Large Language Models (LLMs), Vector DB
• Proficient in English Communication.
• Bachelor’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.

Nice to Have

• A Master’s degree is preferred.
• Proficiency in Excel / Office Applications, data presentation, and business-facing analytics.

Why BOSCH?
Because we don't just follow trends, we create them.
Because together we turn ideas into reality, working every day to make the world of tomorrow a better place. Do you have high standards when it comes to your job? So do we. At Bosch, you will discover more than just work.
Benefits and Career Opportunities

• Working in one of the Best Places to Work in Vietnam
• Join a dynamic and fast growing global company (English-speaking environment)
• 13th-month salary bonus + attractive performance bonus (you'll love it!) + annual performance appraisal
• 100% monthly basic salary and mandatory social insurances in 2-month probation
• Onsite opportunities: short-term and long-term assignments
• 15++ days of annual leave + 1 day of birthday leave
• Premium health insurance for employee and 02 family members
• Flexible working time
• Lunch and parking allowance
• Various training on hot-trend technologies/ foreign language (English/Chinese/Japanese) and soft-skills
• Fitness & sport activities: football, badminton, yoga, Aerobic
• Free in-house entertainment facilities and snack
• Join in various team building, company trip, year-end party, tech talks and a lot of charity events