Data Scientist(Gen AI/LLM)

Data scientists are responsible for using data to solve problems and inform business decisions. This role involves collecting and analyzing data, creating models, communicating findings, and making data-driven recommendations. A successful candidate will leverage predictive modeling, machine learning, and data wrangling techniques to improve the quality of data or product offerings. In addition to technical skills, data scientists must navigate the complexities of data privacy and ethics while communicating their insights to stakeholders. Key Responsibilities:

• Data Collection: Identify available and useful data; collect, categorize, and analyze it.
• Modeling: Create, validate, test, and update algorithms and models for data analysis.
• Data Visualization: Present findings using data visualization software.
• Communication: Communicate recommendations to other teams and senior staff.
• Business Recommendations: Make actionable business recommendations based on data analysis.
• Problem Solving: Utilize data to solve complex company challenges.
• Predictive Modeling: Develop predictive models for forecasting and theorizing.
• Machine Learning: Apply machine learning techniques to enhance data quality or improve product offerings.
• Data Wrangling: Manage and address imperfections in data to ensure accuracy.
• Data Sources: Evaluate the effectiveness of data sources and data-gathering techniques.
• Research & Prototyping: Conduct research to develop prototypes and proof of concepts.
• Data Privacy & Ethics: Ensure compliance with data privacy regulations and navigate ethical concerns in data usage.

Required Skills and Qualifications:

• Strong applied statistical and mathematical skills.
• Expertise in machine learning methods.
• Proficiency in data visualization tools.
• Excellent communication skills to convey complex data insights to non-technical stakeholders.
• Ability to evaluate data sources and manage imperfect datasets.
• A combination of technical skills and business acumen to drive data-driven decisions.

Technical Skills:

• Azure Cloud
• Snowflake
• Artificial Intelligence (AI)
• Large Language Models (LLM)
• RDF Databases
• FastAPI
• LangChain
• Python
• MS SQL
• NoSQL
• ETL/ELT Processes
• SPARQL

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