Data Scientist

Overview

Individuals with 5+ years of experience implementing and managing data science projects. Excellent working knowledge of traditional machine learning and LLM techniques.

The candidate must demonstrate the ability to navigate and advise on complex ML ecosystems from a model building and evaluation perspective. Experience in NLP and chatbots domains is preferred.

We acknowledge the job market is blurring the line between data roles: while software skills are necessary, the emphasis of this position is on data science skills, not on data-, ML- nor software-engineering.

Responsibilities

• Lead data science and machine learning projects, contributing to model development, optimization and evaluation.
• Perform data cleaning, feature engineering, and exploratory data analysis.
• Translate business requirements into technical solutions, document and communicate project progress, manage non-technical stakeholders.
• Collaborate with other DS and engineers to deliver projects.
  
  

• Experience in and understanding of the natural language processing (NLP) and large language model (LLM) landscape.
• Proficiency with Python for data analysis, supervised & unsupervised learning ML tasks.
• Ability to translate complex machine learning problem statements into specific deliverables and requirements.
• Should have worked with major cloud platforms such as AWS, Azure or GCP.
• Working knowledge of SQL and no-SQL databases.
• Ability to create data and ML pipelines for more efficient and repeatable data science projects using MLOps principles.
• Keep abreast with new tools, algorithms and techniques in machine learning and works to implement them in the organization.
• Strong understanding of evaluation and monitoring metrics for machine learning projects.
  
  

• Track record of getting ML models into production
• Experience building chatbots.
• Experience with closed and open source LLMs.
• Experience with frameworks and technologies like scikit-learn, BERT, langchain, autogen…
• Certifications or courses in data science.
  
  

• Master’s/Bachelors/PhD Degree in Computer Science, Engineering, Data Science, or a related field.
  
  

• Understanding of Agile and Scrum methodologies.
• Ability to follow SDLC processes and contribute to technical documentation.
  
  

• Self-motivated and capable of working independently with minimal management supervision.
• Well-developed design, analytical & problem-solving skills
• Excellent communication and interpersonal skills.
• Excellent team player, able to work with virtual teams in several time zones.