AI/ML Tech Partner (USA)

Responsibilities

• 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
• Innovation mindset with a focus on scalable, reusable solutions

Benefits

• Significant career development opportunities
• Part of a small, fast-growing, challenging, and entrepreneurial environment
• 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.