Understand the platform and workflows performed for customers.
Identify opportunities to optimize existing data processes and data structures that support advanced analytics and data science applications.
Work cross-functionally to help translate business requirements and technical specifications into solutions.
Perform exploratory and diagnostic data analysis to identify opportunities for optimization and scaling of information processing and retrieval.
Be responsible for data mining using state-of-the-art methods.
Document requirements and resolve conflicts or ambiguities.
Develop prototypes, technical requirements specifications, and other documentation as required to formalize and communicate design concepts to Software and Data Engineering teams for execution.
Work in a self-directed fashion to work through ambiguities, grasp and implement effective abstractions and solutions, and develop resolutions for technical conflicts.
Report on the results of the analysis in succinct form.
Regularly work with colleagues in US offices (Cambridge, MA and Houston, TX).
Requirements
Good understanding of machine learning techniques and algorithms.
Solid understanding of research design principles.
Knowledge of Software Development Lifecycle.
Strong programming skills in Python.
Experience with JavaScript is a plus.
Hands-on experience with building end-to-end prototypes covering stages from data ingestion and processing to instantiation of interactive UI.
Understanding and experience with LLM OPS workflows, including fine-tuning, inference optimization, integration and monitoring is a plus.
Broad experience with elements of Python’s data science and machine learning ecosystem including NumPy, Pandas/Polars, Jupyter, SciPy, Scikit-Learn, Statsmodels, Altair, etc.
Experience with building applications with Flask, Gradio, Streamlit.
Experience with data visualization tools and frameworks such as Vega/Vega-Lite, D3.js, Plotly, Gephi, Tableau, etc.
Proficiency in using SQL.
Familiarity with graph databases and query languages such as Cypher or Gremlin is a plus.
Conceptual understanding of knowledge graphs and ontologies.
Strong communications skills with technical and non-technical audiences.
Previous experience performing data analysis.
Full stack software experience.
4+ years of experience in a relevant data science role.
Master’s degree in computer science, data analytics, applied mathematics, or related field.
Benefits
Context Labs embraces diversity and equal opportunity.
Reasonable accommodation for individuals with disabilities during the hiring process.
Senior Product Analyst collaborating with teams to develop innovative products at Agência Estado. Key responsibilities include data analysis, market research, and facilitating product management processes.
Senior/Staff Data Scientist developing AI for commerce in the Middle East. Architecting systems for merchant and customer AI assistants and content generation.
Data Scientist leveraging statistical methods and machine learning techniques at FUCHS. Focus on data analysis, modeling, and collaboration for data - driven solutions.
Data Science Intern leveraging AI and ML technologies for product development at Seagate. Hands - on experience with data analysis, model development, and actionable insights generation.
Analyst within Credit Risk Management team identifying credit segmentation opportunities using statistical methods. Collaborating with teams to enhance credit decision process and policies.
Data Manager managing and analyzing company data at Amoddex, a consultancy for IT transformation projects. Ensuring data integrity and supporting strategic decision - making in a collaborative environment.
Data Scientist at Capital One on the LLM Customization Team utilizing the latest in computing and machine learning technologies. Collaborating with data scientists and engineers to deliver AI powered products.
Lead Full Stack Data Scientist at Tilt, building the intelligence layer for data - based decisions. Driving data science strategy and analytics to enhance product and growth insights.
Data Scientist focusing on Generative AI applications and engineering problem - solving at Ford. Collaborating with cross - functional teams to innovate and improve technology solutions in the automotive sector.
AI Engineer/Data Scientist in Ford's Global Data Insights & Analytics team. Developing advanced AI/ML solutions and collaborating on cloud - native data products.