Role Overview
- Act as a trusted advisor to C-level stakeholders, defining AI strategy, roadmaps, and transformation initiatives aligned to business goals
- Lead end-to-end delivery of AI/ML solutions, from data discovery and modeling to deployment, monitoring, and continuous improvement
- Architect and implement scalable data platforms (lakehouse, data mesh) and AI ecosystems leveraging cloud technologies (AWS, GCP, Azure)
- Drive advanced analytics, machine learning, and GenAI use cases, including NLP, forecasting, optimization, and recommendation systems
- Establish and scale MLOps practices, including CI/CD pipelines, model governance, observability, and lifecycle management
- Translate complex business requirements into technical specifications, including data models, STTM, and transformation logic
- Lead large, cross-functional teams across data engineering, data science, and analytics
- Ensure responsible AI practices, including model explainability, fairness, privacy, and regulatory compliance
- Identify new business opportunities, contribute to pre-sales, solutioning, and thought leadership
- Mentor senior talent and build high-performing AI and data teams
Requirements
- 18+ years of experience in AI, data science, analytics, or data engineering, with significant consulting/services background
- Proven track record of leading large-scale AI and data transformation programs for enterprise clients
- Deep expertise in machine learning, statistical modeling, optimization, and AI frameworks (e.g., TensorFlow, PyTorch, scikit-learn)
- Strong programming skills in Python and SQL, with experience in distributed data processing (Spark)
- Extensive experience with modern data platforms and tools (Databricks, Snowflake, BigQuery, dbt)
- Expertise in cloud-native architectures and services across AWS, GCP, or Azure
- Hands-on experience with MLOps tools (MLflow, Kubeflow, Airflow) and production-grade deployments
- Strong understanding of data modeling, ETL/ELT pipelines, and data governance frameworks
- Experience with Generative AI (LLMs, prompt engineering, RAG architectures, vector databases)
- Industry agnostic experience in domains such as Retail, CPG, Insurance, Financial Services, Pharma & Life Science, SaaS, Manufacturing, Telecom, etc.
- Experience with data privacy regulations (GDPR, HIPAA) and AI risk frameworks
- Advanced degree in Computer Science, Data Science, Statistics, or related field
Key Competencies
- Strategic leadership and executive communication
- Deep technical problem-solving and architecture design
- Client relationship management and business development
- Ability to bridge business and technical teams effectively
- Innovation mindset with a focus on scalable, reusable solutions
Tech Stack
- Airflow
- AWS
- Azure
- BigQuery
- Cloud
- ETL
- Google Cloud Platform
- Python
- PyTorch
- Scikit-Learn
- Spark
- SQL
- Tensorflow
Benefits
Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging, and entrepreneurial environment with a high degree of individual responsibility.
Disclaimer
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.