Senior Data Scientist

Experience with supervised learning and neural networks including LSTM and feedforward required. Experience mentoring junior data scientists is also required.

• Culturally, you’ll bring prior experience at another high growth, venture backed tech and/or retail/e-commerce start-up (ideally as part of a small, nimble, cross functional team). You will seek out and thrive in a fast-paced environment with heaps of ambiguity and rapidly changing conditions.
• As a Senior Data Scientist, you will habitually think in a creative / out of the box way in approaching problems and challenge the status quo with ‘first principle thinking’ in everything that you do. A successful candidate will be able to conceptualize a problem from the foundation and be self-directed in terms of execution and overcoming obstacles.
• You are someone who challenges the norm, you will have a proven thought process which naturally gravitates toward framing technical processes and models from the business perspective (i.e. problem, solution, impact).
• You are comfortable developing models by taking the quickest path possible and subsequently migrating those models to production, at ease continuously iterating and improving in quick cycles.
• As a leader on the team, the role will entail mentoring junior data scientists including unblocking them on any ongoing technical challenges they face and further support the CTO in ensuring projects are on schedule and as scoped.
• This role will report directly into the CTO based in New York. Initially you’d join as a 90-day Contractor with a view to becoming a FT (Full Time) employee at the end of the term.

The key areas of expertise encompass 4 general areas:

• Comfort with scoping and solving machine learning problems independently
• Retail experience
• Experience building models and happy prototyping and moving into production.
• Product Recommender (algorithm), Propensity Modeling, Contextual Bandits, Collaborative Filtering, and Market Basket Analysis (with experience of working with CPG and retail brands)

As well as other areas which include…

• Minimum degree: Masters in a quantitative field such as Statistics, Computer Science, Math
• Incorporated customer and content embeddings to produce personalized rankings
• Built multi-armed bandit models to continually explore and value content
• Developed causal estimates of incremental value (lift) of displaying content
• Developed models to set pricing guardrails
• Built and deployed cold-start pricing optimization solutions
• Led or been part of projects to build and deploy automated customer service ticket routing (or similar products) using NLP
• Designed and prototyped a deep learning based personalized multi-entity search relevance systems
• Built causal models for offline (in-store) conversion lift driven by mobile ad exposure
• Matrix Factorization, Neural Networks (LSTM, Feedforward), Clustering Algorithm, Latent Feature Modeling, Next Best Action Modeling, Deep Reinforcement Learning, Natural Language Processing (NLP), A/B Testing and Incrementality Testing
• Proficiency in ML or Deep Learning with Python packages such as such as Sci-Kit Learn, Tensorflow or Keras
• Proven expertise in data cleaning and EDA in Python with packages such as Pandas, Numpy, plotly, seaborn, matplotlib

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