PRISTINE IS LOOKING FOR – Principal AI Scientist
Can you architect real-time optimized recommendation engines leveraging cognitive, prescriptive, explainable AI? Can you develop self-learning models? Can you envision automating creativity? Do you wish to immerse yourself in a high-speed, small team of Retail Business Experts, AI, Behavioral & Cognitive Scientists, CX Designers, and Solution Engineers? Do you possess exceptional abstract thinking and conceptual abilities? Can you transform the abstract into a pragmatic solution? Are you very curious? Are you a ‘make-it-happen’ person?
Pristine is looking for you. Pristine’s pioneering AI technology delivers an optimal experience for each individual customer of our retail and CPG clients. To survive & thrive, our clients need to transform their businesses rapidly and deliver purposeful customer experiences. This customer experience covers Product, Presentation, Pricing and Fulfillment. Every day, our SaaS platform receives and learns from 30 million+ new customer interactions, representing 12,000 stores/websites and 30 million customers. We are looking for exceptional Principal AI Scientists to rapidly advance our solutions and strengthen our leadership. For this role, we are looking for leaders with solid foundation in AI, Mathematics, or Computer Science with proven solution life cycle implementation experience.
Send your resume to firstname.lastname@example.org. Please describe in a few sentences what makes you supremely qualified for this role.
- Role: Principal AI Scientist
- Experience: 3 to 5 years
- Qualification: PhD in AI, Comp Science, Math or Stats from exceptional institutions
- Contribute to sophisticated Customer Experience modeling.
- Contribute to prescriptive modeling life cycle and optimize the end-to-end pipeline.
- Partner with Customers, Retail Experts, AI Scientists, Behavioral & Cognitive Scientists, CX Designers, and Solution Engineers.
- Understand business challenges, ask the right questions, define precise problem statements, develop solution approaches that advance the state of the art, solve critical technical problems, lead the team and rapidly deliver effective solutions.
- Communicate business analysis and results to stakeholders using effective visuals and succinct documents.
- Nurture team members.
- Facilitate a positive, open work culture characterized by idea exchange, constructive peer review, co-creation, and relentless advancement.
- Implementing a variety of AI techniques from basic descriptive statistics, hypothesis testing, feature transformation to dimensionality reduction, supervised or unsupervised learning, model tuning, and validation.
- Designing, training and evaluating sophisticated models. Modelling complex feature sets.
- Leveraging methods like Transfer Learning, Dimensionality Reduction and ProdtoVec.
- Complete AI lifecycle contribution – problem identification & statement, solution approach development, data prep, analysis, visualization, algorithm development & implementation, measurement, validation & presentation, and improvement.
- Effectively communicating complex concepts to technical and non-technical audiences.
- Working with colleagues across multicultural global offices.
- Supervised and Unsupervised Machine Learning algorithms.
- GAN, ANN, RNN, GNN, Transfer Learning, Generative AI, NLU, Combinatorial Optimization.
- Causal Inferencing, A/B Testing.
- AI Search algorithms.
- Gradient Descent, Multi-objective optimization, Combinatorial Optimization.
- AI Search algorithms
- Python and/or R.
- TensorFlow, Pytorch, SkLearn.