About the job:
You will be part of the leadership team and will be expected to manage ambiguity & help senior leadership optimize business goals as a whole.
You need to be very strong in Statistics, Data science, Business Analytics, Machine Learning and ultimately building strong business value using these levers. You should have successfully built and managed highly performant teams of at least 10+ AI/ML, GenAI and LLM Engineers in the past, preferably even larger teams.
Additionally we strongly value those who have some prior experience working at a data science consulting firm, and building a function that offers similar services to your clients, assisting with technical sales, team building, successful project delivery, expansion planning, identifying POC opportunities, growing client accounts and taking P&L ownership.
Minimum qualifications:
Master’s degree in Computer Science, Statistics, Data Science or other relevant engineering discipline, or equivalent practical experience.
7+ years of Data Science experience and at least 3 years of experience in a leadership role demonstrating a high level of ownership and responsibility.
Should have managed AI/ML, GenAI and LLM teams of minimum 10+ in size.
Experience with technical innovation within cross-functional engineering environments.
Experience growing and scaling teams, and motivating others by creating a shared sense of purpose.
Must Have:
Strong expertise with data analytics and business analytics.
Experience solving problems for various business divisions.
Experience managing companies along an ML/data roadmap from ground zero even when they have no clear strategy in place.
Planning and successfully executing a strategy involving appropriate building of GenAI products, logging the right data, acquiring the data or running a data labeling process.
Expertise with ML/MLOps in both predictive modeling as well as modern techniques.
Nice to have:
Drive technical pre-sales activities by leading client discovery, proposals, and proof-of-concepts.
Assess client needs for scoping, cultivate relationships, and create reusable assets to expedite pre-sales and delivery.
Any industry specialization will be a good to have