AI/ML Tech Partner (USA)

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Various market research firms, including Forrester and Gartner, has recognized our business value and leadership. We are headquartered in Silicon Valley and have our global delivery center in Chennai, India. If you are passionate about working on unstructured business problems that can be solved using data and are excited about building, leading, and enabling a team of analytics professionals toward that objective, we would like to talk to you. We are seeking a highly experienced AI Tech Partner with 18+ years of experience to lead enterprise-scale AI and data transformation initiatives. This role blends deep technical expertise with strategic business leadership to drive innovation, build scalable AI ecosystems, and deliver measurable business value across client engagements. 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 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 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.