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Tech Stack
Tools & technologiesCloudMicroservicesPySparkPythonSQL
About the role
Key responsibilities & impact- Translate business goals into analytical problems; Identify optimal algorithms, statistical techniques and/or GenAI architecture suitable for the business problem at hand
- Work in cross-functional teams to develop ML/data science products, including GenAI applications
- Apply best-in-breed data science techniques including descriptive, predictive, and machine learning methods from design to implementation
- Focus on feature engineering, model training, model evaluation, and prompt engineering for LLMs
- Design, develop, and deploy GenAI solutions including AI agents, chatbots, and autonomous systems that solve complex business problems
- Research and pilot the latest GenAI technologies, RAG (Retrieval-Augmented Generation) techniques, and agentic frameworks (LangChain, LangGraph, CrewAI etc.)
- Implement AI bots/agents with advanced reasoning capabilities and tool use patterns
- Work with vector databases and embedding models to build intelligent information retrieval systems
- Break down broader data science development milestones into actionable goals, activities, and work plans
- Create and maintain technical design artifacts describing application functionality, data models, interfaces, and integrations
- Engage and negotiate with stakeholders, make business recommendations with effective presentations of findings at multiple levels of stakeholders
- Champion continuous improvement and foster innovation within the analytics community.
Requirements
What you’ll need- Bachelor’s degree in computer science, Statistics, Mathematics, or related field, or equivalent experience
- 5+ years experience in developing and implementing data science techniques
- Proficient in Python for data science and GenAI application development
- Experience with writing complex SQL and PySpark queries to extract and integrate data from multiple database sources
- Proficiency in machine learning including supervised and unsupervised models
- Demonstrated experience in data transformation, data manipulation, and working with structured vs. unstructured data
- Strong understanding of APIs, microservices architecture, and cloud-native development
- Hands-on expertise with GenAI frameworks and LLM APIs with experience developing AI bots/agents with reasoning and tool-use capabilities
- Strong understanding of RAG techniques, prompt engineering, and fine-tuning methodologies and familiarity with vector databases and embedding models
- Experience with chatbot development concepts and conversational AI design
- Exceptional communication skills to articulate complex technical concepts to both technical and non-technical stakeholders
- Effective and concise oral and written storytelling and insights communication skills
- Ability to work on multiple projects in parallel while managing constantly changing deadlines and priorities
- Proven ability to mentor and guide junior data scientists and data engineers
- Strong problem-solving abilities and analytical skills with keen attention to detail.
Benefits
Comp & perks- Wellness programs that support the three pillars of your health – mental, physical, and financial
- Flexible work arrangements
- The opportunity to move along a variety of career paths with amazing networking potential.
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Data Science TechniquesFeature EngineeringModel TrainingModel EvaluationData TransformationData ManipulationAPIs UnderstandingMicroservices ArchitectureRAG TechniquesPrompt Engineering
Soft Skills
Exceptional Communication SkillsEffective StorytellingProblem-Solving AbilitiesAnalytical SkillsMentoring and Guiding