Data Scientist Lead LLM, Generative AI, ML

Top 3 Reasons To Join Us
Professional and flexible working environment
Career development and international assignments
Attractive salary and reward initiatives
The Job

Responsible for the full lifecycle of analytical and machine learning model development, leading and supporting the team while contributing hands-on across all phases, from ideation and experimentation to implementation, testing, deployment, and optimization.

Responsibilities

• Lead and oversee the Data Science team across research, development, evaluation, fine-tuning, and deployment of ML and generative AI models, including statistical analysis, feature engineering, and hands-on contribution when needed
• Guide the design, implementation, and optimization of robust data pipelines and ML system architectures in collaboration with Data Engineering, ensuring scalability for both real-time and batch use cases
• Provide direction for creating analytical reports, dashboards, and model-driven visual insights to effectively communicate findings to business stakeholders
• Establish and enforce MLOps and technical quality standards - including model versioning, reproducibility, observability, governance, ensuring the team consistently follows these standards and providing guidance to help them apply the practices effectively
• Perform solution reviews, code reviews, and model validation to ensure consistent delivery quality
• Lead technical discussions with the team and clients, provide effort estimations, deliver technical training
• Support the PM with source-control and technical governance strategies

Your Skills and Experience

Technical Skills

• 5+ years of hands‐on experience in Data Science, ML, or Applied AI
• Proficiency in Python (e.g., Pandas, NumPy, FastAPI)
• Strong experience with SQL and working with relational and NoSQL databases
• Good knowledge of big data technologies (e.g., Spark, Databricks, Delta Lake, Kafka)
• Experience with at least one Cloud provider (e.g., Azure, AWS, or GCP)
• Experience using data visualization / BI tools such as Power BI, Tableau, or open-source BI tools
• Solid knowledge and hands-on experience with key machine learning algorithms such as classification, regression, clustering, time series forecasting, and anomaly detection using tools like Scikit-learn, PyTorch, and TensorFlow
• Strong foundation in machine learning concepts and deep learning (e.g., CNNs, RNNs, Transformers)

Math & Statistical Knowledge

• Strong foundation in probability, statistics, optimization, and linear algebra
• Experience in designing experiments (e.g., A/B testing) and interpreting statistical significance
• Ability to apply math-driven thinking to AI/ML model design

Domain Knowledge

• Experience with one of the following domains such as media, banking, finance, healthcare, retail, manufacturing, or insurance
• Ability to understand and interpret domain-specific business problems and translate them into data science solutions

English Requirements

• Good communication skills in English, both written and verbal

Soft Skills

• Strong problem-solving and critical thinking abilities
• Ability to clearly communicate technical findings to non-technical stakeholders
• Collaborative, agile mindset with a self-starter attitude
• Comfortable working in fast-paced, cross-functional teams

Nice to have

• Experience with ETL tools (Airflow, DBT, Azure Data Factory, or AWS Glue)
• Experience with MLOps tools (e.g., MLflow, SageMaker, Azure ML, Vertex AI)
• Generative AI Skills
• Awareness or working knowledge of LLMs (e.g., GPT-4, Claude, LLaMA, Mistral)
• Exposure to GenAI frameworks such as LangChain, LlamaIndex, or Hugging Face Transformers
• Understanding of prompt engineering, embeddings, and concepts like RAG
• Familiarity with GenAI use cases such as summarization, document analysis, chatbots, or code generation
• Ability to integrate GenAI APIs (OpenAI, Azure OpenAI, Hugging Face) into applications

Why You'll Love Working Here

• 13 month salary per year
• Performance bonus (up to 2-month salary)
• Flexible option bonus for good performers & retention bonus for outstanding performers
• Social - Health - Insurance paid fully
• Healthcare: Annual health check-up, Premium Health Insurance (plus 1 slot for your dependent)
• Annual leaves: 14 - 18 days
• Clubs program: Football, Badminton, Swimming, Tennis, Rock, Yoga...
• Training courses: Technical skills - Soft skills - English

People are extremely important to us and that's why we have a clear vision: to make NashTech a great place to work in its sector. We pride ourselves on:

• Professional and Flexible Working Environment
• Great Teamwork
• International Assignments
• WeCare - WeShare - WeDare - WeInnovate Engagement Program