Senior Data Architect – Pre-sales, Solutions

This is a fully remote position, open to applicants in India.

📋 Description

• Act as a senior trusted advisor to the CIO, CTO, CDO, CRO, as well as business, product, and technology stakeholders.

• Drive Data & AI exploration and convert ambiguous business challenges into quantifiable, production-ready solutions.

• Architect comprehensive systems that encompass data platforms, analytics, machine learning, GenAI, applications, APIs, governance, and integrations.

• Oversee and challenge sophisticated forecasting and predictive modeling methodologies.

• Establish success metrics for business and models, including R², WAPE, MAPE, statistical significance, and business-impact KPIs.

• Ensure accuracy at specific points in time, avert data leakage, and uphold stringent model development and validation standards.

• Offer hands-on technical guidance utilizing Python, SQL, Snowflake, notebooks, Git, and contemporary Data/AI platforms.

• Develop AI use cases in areas such as forecasting, sponsorship sales, lead scoring, next-best-action, revenue intelligence, personalization, subscription growth, and commercial optimization.

• Assess whether classical analytics/ML, GenAI, or agentic AI is the suitable solution for a given problem.

• Facilitate architecture and solution-design workshops, presenting findings to senior and executive stakeholders.

• Assist with proposals, SOWs, RFI/RFP responses, estimates, staffing models, and the shaping of technical solutions.

• Lead and mentor cross-disciplinary teams in Data Science, Data Engineering, AI Engineering, Software Engineering, and Architecture.

• Engage in client stand-ups, backlog refinement, executive updates, and strategic planning sessions.

• Educate and share knowledge with client teams; ensure proper documentation, reproducibility, and transition.

• Challenge client requests when proposed methods do not address the core business issue.

• Attend internal and external meetings via video calls as required.

⛳️ Requirements

• Minimum of 5 years of hands-on experience in forecasting and data domains.

• Demonstrated success in leading at least two similar forecasting projects from initial discovery to production/handover.

• Extensive experience with comparable-unit or same-store forecasting techniques.

• Expert in multivariable regression, collinearity analysis, VIF interpretation, model tuning, selection, and holdout validation.

• Strong comprehension of sparse and zero-inflated datasets; must recognize why nulls should not be treated as zero.

• Proficient in metrics such as R², WAPE, MAPE, and p-values.

• In-depth understanding of data leakage and the importance of point-in-time feature correctness.

• Strong skills in Python and SQL, with experience in developing reproducible analytical workflows/notebooks.

• Experience with Git and pull-request-based software delivery methodologies.

• Solid capabilities in Data Architecture and Solution Architecture, covering ingestion, transformation, modeling, security, governance, APIs, cloud, and production operations.

• Thorough understanding of ML, GenAI/LLMs, RAG, AI agents, and contemporary enterprise AI methodologies.

• Proven ability to communicate effectively with executives, including presenting to non-statistical audiences by prioritizing business outcomes over methodology.

• Capability to clearly articulate forecast/model limitations, uncertainties, and risks in straightforward language.

• Established client consulting and thought-leadership experience; able to impart methodology knowledge, not just execute it.

• History of leading senior client workshops, technical discovery, architecture discussions, and executive presentations.

• Strong commercial insight and ability to link technical decisions to revenue, operational, or customer results.

• Preferred experience in industries such as sports, media, entertainment, streaming, ticketing, subscriptions, sponsorship, advertising, telecom, or commercial/revenue analytics.

• Desired experience with hierarchical/mixed-effects modeling, ADRs, large-scale categorical encoding, MLOps, governance, and responsible AI practices.

• Proficient in Snowflake; experience with Snowflake ML / Model Registry is a plus.

• 10–12+ years of overall experience in Data, Analytics, AI, Architecture, or related technology fields.

• Willingness to work onsite at corporate or client offices as needed.

• For roles that necessitate business travel and/or event participation, a valid driver’s license and a satisfactory driving record are required.

🏝️ Benefits

• Comprehensive healthcare and benefits package, including Medical, Dental, Vision, Disability coverage, and various other options.

• Flexible Spending Accounts for Medical, Transit, and Dependent Care expenses.

• Employer-paid Life Insurance and AD&D coverage.

• Health Savings Account in conjunction with our low-cost High Deductible Medical Plan.

• 401(k) Safe Harbor Retirement plan with employer matching and immediate vesting.

• Reasonable accommodations available during the recruitment process upon request.