Director - Presales (Data Science)
3 weeks ago
About the Role: We are seeking a dynamic and results-driven Director - Presales (Data Science) to lead the technical solutioning and consultative sales process for our Data Science and AI/ML offerings. This role demands a unique blend of strong technical acumen in advanced analytics, machine learning, and data science, coupled with deep experience in client-facing presales activities across verticals. As the Director, you will partner closely with Sales, Delivery, and Product teams to articulate the business value of our solutions to clients, design winning proposals, and drive strategic engagements from early-stage conversations to deal closure.
Key Responsibilities:
- Lead presales engagements for Data Science, Advanced Analytics, and AI/ML initiatives across industries (e.g., Retail, BFSI, Healthcare, Manufacturing, etc.).
- Translate business problems into data science solutions using Gen AI, Classical ML, statistical modeling, forecasting, and optimization techniques.
- Own and deliver solution architecture, PoCs, and technical deep-dives during client discussions and RFP/RFI responses.
- Collaborate with Sales to shape client strategy and proactively identify new opportunities within accounts.
- Develop reusable solution frameworks and assets to accelerate presales cycles.
- Partner with Delivery and Practice leaders to estimate effort, define implementation plans, and ensure feasibility.
- Evangelize our Data Science capabilities through client workshops, thought leadership, and industry events.
- Manage and mentor a small team of presales solution architects or data scientists as needed.
Required Qualifications:
- 15-20 years of total experience, with 8+ years in Data Science / Machine Learning roles and 4+ years in Presales, Solutioning, or Customer-facing technical roles.
- Proven track record of designing and pitching complex data science solutions in a presales context.
- Strong hands-on understanding of algorithms in supervised/unsupervised learning, NLP, GenAI, time-series forecasting, and optimization.
- Familiarity with tech stacks such as Python, R, SQL, PySpark, and cloud platforms like AWS, Azure, or GCP.
- Experience working with cross-functional stakeholders including sales, product, delivery, and CXOs.
- Excellent communication, presentation, and storytelling skills with the ability to simplify complex concepts.
- Experience handling large enterprise clients, preferably across multiple verticals
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