Associate Data Scientist building predictive models and AI applications for AlgaeCal’s clinically backed natural bone - loss solution. Turning large datasets into strategies that improve efficiency, sales, and profitability.
About the role
- Senior Data Scientist at Hungryroot, owning machine learning to personalize customer deliveries. Collaborates within a remote-first team to optimize data models and improve customer satisfaction.
Responsibilities
- Separate durable preference from noise. Design robust feature representations from high-cardinality, implicit behavioral data (swaps, skips, saves) to capture true user intent and predict future engagement.
- Model temporal dynamics and changing tastes. Architect sequential and recency-aware systems that adapt to shifting user preferences, ensuring recommendations reflect current intent rather than stale history.
- Solve the cold-start problem. Leverage cohort signals, clustering, and content embeddings to generalize learnings across users, ensuring that even a new customer’s first box feels deeply personalized.
- Bridge ML and constrained optimization. Integrate model scores (e.g., predicted conversion) with operations-research engines to perform business-aware re-ranking, balancing personalization with hard constraints like diet, budget, and inventory.
- Advance the modeling. Evolve our systems using the architectures that drive modern, high-scale personalization, such as multi-stage retrieval and ranking, learning-to-rank (LTR), matrix factorization, and gradient-boosted trees. You will also evaluate and integrate more sophisticated techniques (like contextual bandits or sequence modeling) as our data complexity grows.
- Drive rigorous experimentation. Define robust offline evaluation metrics (e.g., NDCG, MAP) and design online A/B tests to measure true causal impact on customer retention and satisfaction
Requirements
- 5+ years of hands-on experience in data science, applied machine learning, or a related quantitative role.
- Champion ML system best practices. You treat the ML lifecycle as a rigorous discipline, moving systematically from problem definition and feature engineering to robust offline evaluation, online experimentation, and CI/CD for ML.
- Deep expertise in personalization, search ranking, or recommender systems, with hands-on experience building multi-stage architectures (candidate generation, scoring, and re-ranking).
- Strong grounding in statistics, causal inference, and experimentation, with the ability to define proxy metrics and design tests that measure long-term business impact.
- Production-level engineering skills in Python and SQL, with hands-on experience scaling models using big data frameworks and an understanding of system latency trade-offs.
- A commercial mindset to translate complex business constraints into scalable ML architectures.
- Clear communication and a collaborative, remote-friendly working style, including mentoring others.
Benefits
- Remote-first: work from home, work from our NYC office, work from anywhere in the U.S. - you decide!
- Equity
- Unlimited vacation policy
- Universal paid parental leave
- Monthly Hungryroot credit for delicious, healthy groceries
- Comprehensive health, vision, dental, and life insurance
- 401k with Company Match
- A work from home stipend to support your initial home-office setup
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
Report this job
Found something wrong with the page? Please let us know by submitting a report below.
Senior Data Scientist building real - time courier pay and dynamic pricing models for Just Eat Takeaway.com. Optimizing marketplace efficiency and earnings fairness through machine learning and experimentation.
Staff Data Scientist advancing Reddit’s ads measurement, identity, and privacy intelligence. Designing experimentation, identity - resolution, and predictive - modeling methodologies for advertisers.
Data Scientist building production ML, NLP, and GenAI solutions for Irth’s critical - infrastructure SaaS platform. Developing Databricks pipelines and maintainable software for damage prevention and asset integrity.
Junior data scientist supporting derivatives, VaR, stress testing, and regulatory risk models at Desjardins. Implementing methodologies and risk - system products in a hybrid Montréal role.
Evaluating data science and quantitative AI outputs for Gramian Consultancy, an IT professional services and engineering talent consultancy. Creating prompts, datasets, and feedback to improve AI models.
Data Scientist structuring medical knowledge and evaluating AI - driven educational products for Lecturio, a global medical and nursing e - learning platform. Developing statistical validation frameworks and Knowledge Graph API integrations.
Credit risk modelling data scientist developing and maintaining models for Desjardins. Guiding risk quantification, credit decisions, compliance, and practitioner - led modelling projects.
Data Scientist developing transactional fraud detection models for Desjardins’ banking and debit payments. Deploying analytics, dashboards, and mitigation strategies to protect members and clients.
Product analytics consultant delivering business insights and dashboards for Allstate Canada’s personal insurance portfolio. Supporting strategic decisions through performance analysis, reporting automation, and stakeholder recommendations.