Serve as the key lead for Gen AI and LLM Ops in the Mars Snacking Community
Applies strong expertise in AI through the use of machine learning, data mining, and statistical models to design, prototype, and build next-generation ML engines and services
Design, architect, and review the technical architecture of data science solutions
Plan and lead data science projects that cover a diverse range of business problems
Serve as a key point of contact with Data Engineering and DevOps teams for solution architecture and infrastructure design
Review the work of team members, identifying optimum methodologies, advising on implementation, and checking business logic
Use machine learning techniques, visualizations, & statistical analysis to gain insight into various data sets – some readily available, and some you create and curate yourself
Collaborate with internal and external teams to ensure we focus on product and service recommendations, and be a key player in our network of talent
Contribute to a high-performing data science function
Create repeatable, interpretable, dynamic, and scalable models that are seamlessly incorporated into analytic data products
Performance Monitoring: Define key performance indicators (KPIs) and implement monitoring systems for deployed data platforms and products to ensure efficient operations, effective support services, and incident management.
Solution ideation and Development: Guide a team of data scientists to create fit-for-purpose solutions using cutting-edge analytical and AI methodologies.
Focus on setting up a Data Science AI program and delivery methodology: Entails recruiting and forming a team to solve a specific problem; elaborating on a programmatic mindset and tracking value delivery
Requirements & Skills:
7+ years of experience working in a quantitative role, preferably in the CPG or retail industry.
4+ years of experience managing a team of data scientists, product analysts, or data analysts
Proven track record of delivering value through AI/ Data Science products in a fast-paced, agile environment using a scalable and reusable codebase and models to address business problems effectively.
Partner with business leadership across functions to identify business challenges and opportunities and translate them into actionable, integrated, data-driven solutions.
An expert understanding of LLMs, ML Ops, LLM Ops, and pertinent design architecture elements.
An understanding of product management principles such as product definition, roadmap building and management, and product releases and commercialization
Hands-on experience in building Agents and leveraging emerging technologies within Microsoft and Google to design an agentic ecosystem.
A strong customer-centric mindset, especially within an internal customer base with the purpose of driving value creation, adoption, and use
Strategic thinking, problem solving, and innovation, with the ability to anticipate and navigate challenges and opportunities.
Ensure compliance with analytics standards, including tailoring methodologies to specific use case needs such as ML, AI, and descriptive analytics.
Ability to translate business needs into analytical frameworks & superior verbal and written communication skills
Proficiency and hands-on experience in advanced analytics techniques and machine learning algorithms, including NLP, time-series analysis, and other relevant methods, and willingness to coach data scientists tactically
Working understanding of ML Ops and DevOps frameworks
Working expertise of OpenAI Endpoints, Google Vertex, Google Model Garden, and Microsoft Suite of AI Models.
