Data Analyst - AI & Bedrock Specialization
Job Description: FAS - Data Analyst - AI &
- Bedrock Specialization
About Us
We are seeking a highly experienced and visionary Data Analyst with a deep understanding of artificial intelligence (AI) principles and hands-on expertise with cutting-edge tools like Amazon Bedrock. This role is pivotal in transforming complex datasets into actionable insights, enabling data-driven innovation across our organization.Role Summary
The Lead Data Analyst, AI &- Bedrock Specialization, will be responsible for spearheading advanced data analytics initiatives, leveraging AI and generative AI capabilities, particularly with Amazon Bedrock. With 5+ years of experience, you will lead the design, development, and implementation of sophisticated analytical models, provide strategic insights to stakeholders, and mentor a team of data professionals. This role requires a blend of strong technical skills, business acumen, and a passion for pushing the boundaries of data analysis with AI.
Key Responsibilities
- Strategic Data Analysis &
- Insight Generation:
o Utilize advanced statistical methods, machine learning techniques, and AI-driven approaches to uncover complex patterns and trends in large, diverse datasets.
o Develop and maintain comprehensive dashboards and reports, translating complex data into clear, compelling visualizations and narratives for executive and functional teams.
- AI/ML &
- Generative AI Implementation (Bedrock Focus):
o Design and optimize prompts for Large Language Models (LLMs) to extract meaningful insights from unstructured and semi-structured data within Bedrock.
o Explore and integrate other AI/ML services (e.g., Amazon SageMaker, Amazon Q) to enhance data processing, analysis, and automation workflows.
o Contribute to the development of AI-powered agents and intelligent systems for automated data analysis and anomaly detection.
- Data Governance &
- Quality Assurance:
o Develop and implement robust data cleaning, validation, and transformation processes.
o Establish best practices for data management, security, and governance in collaboration with data engineering teams.
- Technical Leadership &
- Mentorship:
o Collaborate with cross-functional teams, including product, engineering, and business units, to understand requirements and deliver data-driven solutions.
- Research &
- Innovation:
o Proactively identify opportunities to apply emerging technologies to solve complex business challenges.
Required Skills &
- Qualifications:
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field.
- 5+ years of progressive experience as a Data Analyst, Business Intelligence Analyst, or similar role, with a strong portfolio of successful data-driven projects.
- Proven hands-on experience with AI/ML concepts and tools, with a specific focus on Generative AI and Large Language Models (LLMs).
- Demonstrable experience with Amazon Bedrock is essential, including knowledge of its foundation models, prompt engineering, and ability to build AI-powered applications.
- Expert-level proficiency in SQL for data extraction and manipulation from various databases (relational, NoSQL).
- Advanced proficiency in Python (Pandas, NumPy, Scikit-learn, etc.) or R for data analysis, statistical modeling, and scripting.
- Strong experience with data visualization tools such as Tableau, Power BI, Qlik Sense, or similar, with a focus on creating insightful and interactive dashboards.
- Experience with cloud platforms (AWS preferred) and related data services (e.g., S3, Redshift, Glue, Athena).
- Excellent analytical, problem-solving, and critical thinking skills.
- Strong communication and presentation skills, with the ability to convey complex technical findings to non-technical stakeholders.
- Ability to work independently and collaboratively in a fast-paced, evolving environment.
Preferred Qualifications
- Experience with other generative AI frameworks or platforms (e.g., OpenAI, Google Cloud AI).
- Familiarity with data warehousing concepts and ETL/ELT processes.
- Knowledge of big data technologies (e.g., Spark, Hadoop).
- Experience with MLOps practices for deploying and managing AI/ML models.