Data Scientist

As a Data Scientist at our client, you will play a crucial role in developing and implementing state-of-the-art machine learning models for use cases in traffic safety, mobility, and city planning. You exhibit excellent knowledge of the data science and data engineering disciplines, including experience working with large datasets in a Python/SQL environment. You have at least four years of data science experience and at least two years of NLP. You will collaborate with cross-functional teams to enhance our products and services, driving innovation and providing actionable intelligence to meet business goals. If you are passionate about data and are eager to contribute to the success of a startup, we would love to hear from you.

Model Development: Develop and optimize data science models to process, analyze, and extract information from varying data sources, particularly textual.
Machine Learning and AI: Apply machine learning and artificial intelligence techniques to build predictive and prescriptive models.
Data Preprocessing: Clean, preprocess, and transform large datasets to prepare them for analysis and model training.
Feature Engineering: Identify and engineer relevant features to enhance model performance and accuracy.
Model Deployment and Evaluation: Design and implement robust evaluation metrics and frameworks to assess and monitor the performance of machine learning models.
Collaboration: Work closely with cross-functional teams, including engineers, product managers, and domain experts, to understand business requirements and deliver data science solutions that meet those needs.
Research: Stay updated on the latest advancements in NLP and AI research and apply them to real-world problems as needed.

Bachelor's in Computer Science, Data Science, or a related field.
4-6 years of experience in machine learning, artificial intelligence, and data science.
2 years of experience in natural language processing.
Extensive knowledge in Python, SQL, Python data science libraries (Pandas, Numpy, Scikit-learn, etc.), and Python NLP libraries (NLTK, SpaCy, etc.).
Solid understanding of data preprocessing, feature engineering, and model deployment/evaluation.
Strong knowledge of machine learning techniques and AI algorithms.
Preference for experience working with geospatial data (SQL PostGIS, Python GeoPandas, ArcToolbox Deep Learning, etc.)
Preference for experience with transformers and LLMs (HuggingFace, GPT, PyTorch, TensorFlow, etc.) and cloud infrastructure platforms such as Snowflake and AWS.
Demonstrated ability to work in a collaborative team environment.
Excellent communication and data storytelling skills.
Strong problem-solving and analytical skills.
Publication record in relevant conferences or journals is a plus.