Requirements: English
Company: The Data Appeal Company
Region: tuscany, italy , Tuscany
The Data Appeal Company is a high-tech company that transforms geo-spatial, sentiment and market data into compelling, valuable insights that are simple and accessible.
We are a dynamic and rapidly expanding company part of Almawave Group
We are looking for a Data Scientist to join our AI Data Team, where you will develop end-to-end solutions to complex business problems using machine learning, statistics, and data analysis.
As part of our team, you will collaborate closely with system engineers, data scientists, front-end developers, and software engineers to design and implement scalable, high-performance AI-driven solutions.
Your Responsibilities:
- Design, develop, and evaluate innovative predictive models in collaboration with the data team.
- Work with LLM APIs to integrate large language models into data pipelines and applications.
- Benchmark and compare different LLMs in terms of accuracy, latency, and cost-performance trade-offs.
- Process and analyze large datasets using state-of-the-art machine learning technologies.
- Automate data processing workflows and ML model pipelines.
- Write reusable, efficient, and scalable code to improve AI-driven processes.
What Were Looking For:
- 2 years of experience in a similar role.
- STEM degree (Engineering, Physics, Mathematics, Statistics);
- Strong knowledge of statistical testing & inference for KPI extraction from Big Data.
- Solid expertise in SQL and Python.
- Familiarity with data management and numerical computing libraries (Pandas, Dask, NumPy, SciPy, Spark, etc.).
- Experience with ML engines (Jupyter, Google Colab).
- Knowledge of Machine Learning frameworks (Scikit-learn, NLTK, spaCy).
- Hands-on experience in data preparation, feature extraction, and engineering.
- Proficiency in working with LLM APIs (OpenAI GPT, Claude, Mistral, Gemini, Cohere, etc.).
- Understanding of RESTful APIs, including authentication, rate limits, and response parsing.
- Experience with model selection and training, particularly transfer learning.
- A curious, problem-solving mindset and a passion for data science.
Nice-to-Have Skills:
- Big Data experience.
- Knowledge of causal inference for spatial and time-series problems.
- Experience with geospatial analysis for location intelligence.
- Familiarity with transformer architectures like BERT (Hugging Face).
- Understanding of LLM deployment, latency optimization, and cost-efficient scaling strategies.
- Hands-on experience with deep learning frameworks (TensorFlow, Keras, PyTorch).
- Proficiency in Git and version control best practices.
- Experience with Agile methodologies.
- AWS Cloud experience.
Our Tech Stack & Practices:
- Languages: Java, Kotlin (SpringBoot, Quarkus), Golang, Python (Pandas, Dask, NumPy, SciPy).
- Machine Learning: Scikit-learn, NLTK, spaCy, TensorFlow, PyTorch.
- Frontend: TypeScript (Angular, React).
- Cloud & Infrastructure: AWS, Kubernetes, Terraform, CloudFormation.
- Big Data: Trino, Spark, Hive.
- LLM APIs: GPT, Claude, Gemini, Mistral (for NLP, automation, and data processing).
- AI Practices: Prompt engineering & fine-tuning for domain-specific use cases.
- Development Approach: Agile methodologies.