Objective
Dash is seeking an experienced Senior Data Scientist with a deep understanding of AI, machine learning, and natural language processing (NLP). In this role, you will lead data science projects, mentor junior team members, and collaborate with various departments to apply data-driven insights that drive business outcomes.
Essential Functions
- Lead Data Science Initiatives: Oversee data science projects from ideation to deployment, ensuring they align with strategic business objectives.
- Advanced Analytics and Modeling: Develop, refine, and optimize machine learning models to extract insights from complex datasets.
- AI/NLP Development: Utilize state of the art NLP models (e.g., GPT, BERT, T5) to build intelligent applications and automate text processing.
- U.S. Financial Markets: Apply deep knowledge of U.S. Equity and Options Markets, including proficiency in the FIX protocol, Transaction Cost Analysis (TCA), Execution Quality (EQ), and industry-standard execution benchmarks, to enhance data analysis, optimize model development, and drive informed decision-making.
- Cross-functional, collaboration: Work closely with engineering and business teams to implement models and solutions effectively in production environments.
- Mentorship and Guidance: Mentor junior data scientists, fostering a culture of innovation and continuous learning.
- MLOps and Model Deployment: Ensure models are scalable, robust, and secure, with a strong emphasis on MLOps practices.
- Experimental Design: Design and conduct experiments, such as A/B testing, to validate model performances and optimize outcomes.
Qualifications
- Expertise in AI and NLP: Demonstrated experience with Large Language Models (LLMs) and NLP tools, such as GPT, BERT, T5, Hugging Face Transformers, etc.
- Strong Programming Skills: Proficiency in Python and R, with experience in SQL and big data technologies.
- Machine Learning Proficiency: In-depth knowledge of supervised and unsupervised learning, deep learning frameworks (e.g., TensorFlow, PyTorch), model optimization techniques.
- Data Analysis and Visualization: Expertise in exploratory data analysis (EDA) and proficiency in visualization tools (e.g., Matplotlib, Seaborn, Plotly).
- Statistical Competence: Strong foundation in statistical methods, including hypothesis testing, regression analysis, and probability theory.
- MLOps and Data Privacy: experience deploying mode at scale focusing at MLOps practices and ensuring data privacy and security.
- Communication and Leadership: Excellent communication skills and the ability to collaborate effectively across technical and non technical teams.
Preferred Qualifications
- 5-7 years of experience in data science or related roles.
- Advanced degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
- Experience with cloud platforms (AWS, Azure, Google Cloud) and deploying models in distributed computing environments.
