Urgent Middle/Senior Data Scientist

ABOUT THE ROLE

As a Data Scientist, you will play a key role in bridging data science with business value by delivering high-impact solutions across diverse industries. You will work end-to-end-from understanding business requirements to developing models, evaluating outcomes, and deploying scalable solutions-while collaborating with cross-functional teams in a fast-paced, innovation-driven environment.

KEY RESPONSIBILITIES

Your core responsibilities will be tailored to your level of seniority and finalized during the hiring process.

• Discovery and Strategy to Frame Technical Feasibility.
• Solution Architecture & Design: Design robust, scalable, and innovative data science solutions while considering performance, maintainability, and business impact.
• Technical Leadership: Provide technical leadership on complex projects, oversee the work of junior and mid-level data scientists, and ensure best practices are followed.
• End-to-End Project Execution: Take ownership of data science projects and modules, from data collection and preparation to model development, evaluation, and MLOps.
• Communication & Storytelling: Effectively communicate complex analytical concepts and findings to both technical and non-technical stakeholders, translating insights into actionable business recommendations.
• Cross-functional Collaboration: Work closely with project managers, engineers, and business stakeholders to align data science efforts with business objectives.
• Stakeholder Management: Engage with senior stakeholders across the organization to understand business needs, present complex findings, and influence data-driven decision-making at a strategic level.
• Innovation & Research: Stay abreast of the latest advancements in data science, machine learning, and AI, exploring opportunities to integrate new technologies and methodologies.
• Mentorship & Coaching: Actively mentor and coach Data Scientists at all levels, fostering a culture of continuous learning and growth within the team.

QUALIFICATIONS & SKILLS

• Education: Bachelor's degree in Mathematics, Statistics, Data Science, Computer Science, AI, Engineering, or a highly related field is required. A Master's degree in any of the above disciplines is preferred.
• Experience: Possess at least 3 years of experience in one or more data science domains such as machine learning, deep learning, natural language processing (NLP), computer vision (CV), optimization, or statistics.
• Good problem-solving, with the ability to formulate business problems into technical requirements in a scientifically rigorous and effective manner.
• Proficient in English communication skills, especially when engaging with non-technical business stakeholders.
• Expert in Python and SQL along with relevant data science libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, etc.) and the ability to write production-ready code.
• Advanced skills in version control (e.g. GitHub, GitLab, etc.) and data visualization.
• Experience with MLOps tools and practices (e.g., pretraining, model tuning, model packaging, CI/CD for ML, model monitoring, ML pipelines, etc.).
• Hands-on experience with cloud platforms (e.g., GCP, AWS, Azure) and containerization (e.g., Docker, Kubernetes).

BENEFIT:

• Group benefit (Lunch support, Gasoline support).
• Working days/week (From Monday to Friday).
• 2 days WFH/week.
• Health, Social, and Unemployment Insurance (based on full contractual salary, according to Labor Code) and PVI Health Insurance, yearly health-checkup.
• 13th-month salary and performance bonus.
• 12 days annual leave plus extra 02 days of company leave and national holiday leaves.
• Technical certificate fee support.
• Project allowance if any.
• Company trips, sponsored team building, monthly Happy Hour, Sports Clubs (Soccer, Badminton, Ping-Pong, Yoga), and other joyful events.