Full-Time Associate Data Scientist

As an Associate Data Scientist, you will support the development of AI solutions by working on data preparation, model experimentation, and prototyping of LLM-based applications. You’ll collaborate with cross-functional teams, contribute to documentation and reproducible workflows, and stay updated on the latest advancements in generative AI. Under the guidance of senior experts, you’ll help translate business and research questions into data-driven solutions while upholding ethical standards and promoting inclusive practices.

ESSENTIAL DUTIES AND RESPONSIBILITIES:

• Support in the collection, cleaning, and transformation of structured and unstructured datasets.
• Assist in developing, testing, and evaluating predictive and generative models.
• Contribute to the prototyping of LLM-based applications, including chatbots, copilots, or information retrieval system.
• Collaborate with cross-functional teams on applied AI use cases.
• Document workflows, results, and findings for internal reports or external dissemination.
• Work under the supervision of senior data scientists or AI researchers to execute well-defined tasks.
• Ensure reproducibility and code quality in data workflows and model development.
• Keep up to date with recent advancements in generative AI, LLM architectures, and agent-based frameworks.
• Translate business or research questions into analytical problems and propose data-driven solutions.
• Maintain ethical standards and data privacy principles in all stages of analysis and modeling.
• Demonstrate a commitment to diversity, equity, and inclusion through continuous development, modeling inclusive behaviors, and proactively managing bias.
• All other duties as assigned

MINIMUM KNOWLEDGE, SKILLS AND ABILITIES:

• Programming Languages: Python (mandatory), R, SQL; familiarity with Git and Jupyter notebooks.
• Data Analysis & Visualization: Pandas, NumPy, matplotlib, Plotly, Excel, PowerBI
• Machine Learning: Basic understanding of supervised and unsupervised learning; initial experience with Scikit-learn, XGBoost, or similar libraries.
• LLM/RAG: Introductory knowledge of transformer-based models (e.g., BERT, GPT). Familiar with using LLM APIs (e.g., OpenAI, HuggingFace) for text generation, classification, summarization. Exposure to prompt engineering and fine-tuning workflows. Experience integrating RAG pipelines using tools such as LangChain, or LlamaIndex.
• Databases: Familiar with SQL (PostgreSQL, MySQL) and possibly exposure to NoSQL systems (MongoDB).
• Cloud & Tools (optional): Exposure to platforms like AWS, Azure, or GCP; basic use of Docker is a plus.
• Version Control: Basic proficiency with Git/GitHub.
• Strong analytical mindset with attention to detail.
• Comfortable working in cross-functional teams and under the mentorship of senior data scientists.
• Effective communicator of technical findings to both technical and non-technical audiences.
• Fluent English (B2/C1)

PREFERRED QUALIFICATIONS:

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, or related fields.
• Solid foundation in probability, statistics, linear algebra, machine learning, and natural language programming.
• Optional coursework or certifications in Data Analytics, Artificial Intelligence, or Big Data technologies.
• 2/3 years of experience in a related fields.
• Academic projects or thesis involving data preprocessing, exploratory analysis, model development or language processing.
• Experience presenting insights through dashboards, written reports, or oral presentations.

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