Description review
Lead Data Scientist
George Bernard Consulting · Sri Lanka · back to the listing
HR standards
45/100
poor
Title ↔ description
52/100
needs work
Reads as
Machine Learning Engineer
99% confident
What this role officially is
data scientist — ESCO, the EU occupation classification
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist
How others title the same work
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Startups
- Attendi | Medior Machine Learning Engineer | Amsterdam, Netherlands | ONSITE (hybrid) | €6,000 - €7,000 per month | Full-time (80–100%, ~4–5 days/week) | Visa sponsorship + 30% ruling possible Attendi
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What the listing never says
- 18 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
- No section describes what the person would actually do. Scope clarity
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
- No location or timezone policy stated, so a candidate cannot tell where they may work from. Scope clarity
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
• Develop and maintain scalable applications using Python, following best practices for clean, efficient, and maintainable code.
• Build APIs and backend services using modern frameworks such as Flask, FastAPI, or Django.
• Work with containerization and orchestration technologies to support deployment and scalability of applications.
• Design, develop, and deploy GenAI and LLM-based solutions using frameworks such as LangChain and LangGraph.
• Apply prompt engineering techniques and support LLM fine-tuning to optimize model performance.
• Build and optimize data pipelines and perform data processing and transformation using tools like Pandas, NumPy, SQL, and ideally PySpark.
• Translate business requirements into scalable, production-ready technical solutions.
• Collaborate with cross-functional and offshore teams, including UK-based stakeholders, ensuring clear communication and alignment.
• Manage multiple projects in a fast-paced environment while maintaining delivery quality and timelines.
Requirements
• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related discipline.
• Minimum 3+ years of experience in software engineering, data science, machine learning, or AI engineering roles.
• Strong proficiency in Python with hands-on experience in backend development and API frameworks.
• Experience in deploying GenAI/LLM applications in production environments.
• Solid understanding of containerization, CI/CD pipelines, and modern deployment practices.
• Experience working with cloud platforms, preferably Azure, along with Databricks exposure.
• Strong skills in data manipulation and analysis using Pandas, NumPy, SQL, and PySpark (preferred).
• Familiarity with distributed data processing frameworks such as Spark is an added advantage.
• Excellent communication and collaboration skills, especially in distributed/offshore team environments.
Originally posted on Himalayas
• Build APIs and backend services using modern frameworks such as Flask, FastAPI, or Django.
• Work with containerization and orchestration technologies to support deployment and scalability of applications.
• Design, develop, and deploy GenAI and LLM-based solutions using frameworks such as LangChain and LangGraph.
• Apply prompt engineering techniques and support LLM fine-tuning to optimize model performance.
• Build and optimize data pipelines and perform data processing and transformation using tools like Pandas, NumPy, SQL, and ideally PySpark.
• Translate business requirements into scalable, production-ready technical solutions.
• Collaborate with cross-functional and offshore teams, including UK-based stakeholders, ensuring clear communication and alignment.
• Manage multiple projects in a fast-paced environment while maintaining delivery quality and timelines.
Requirements
• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related discipline.
• Minimum 3+ years of experience in software engineering, data science, machine learning, or AI engineering roles.
• Strong proficiency in Python with hands-on experience in backend development and API frameworks.
• Experience in deploying GenAI/LLM applications in production environments.
• Solid understanding of containerization, CI/CD pipelines, and modern deployment practices.
• Experience working with cloud platforms, preferably Azure, along with Databricks exposure.
• Strong skills in data manipulation and analysis using Pandas, NumPy, SQL, and PySpark (preferred).
• Familiarity with distributed data processing frameworks such as Spark is an added advantage.
• Excellent communication and collaboration skills, especially in distributed/offshore team environments.
Originally posted on Himalayas