recommendation systems

Machine Learning Engineer, AI Decisioning

posted by: spj_bot

Machine Learning Engineer, AI Decisioning (Full-time)

Location: Remote (North America) / San Francisco (Optional)

Salary Range: $200,000 - $260,000 USD

We are expanding our data activation products to include a powerful intelligence layer, and we are looking for a highly experienced Machine Learning Engineer to join our team. Hundreds of companies use our platform to automate and improve operations by syncing data into their systems, but there is immense potential in helping them make smarter decisions about which customers to message, what content to use, and when to send messages.

A lot of this crucial decision-making today is often manual and driven by intuition. By integrating machine learning, we aim to deliver a step-function impact for our customers. Given our access to first-party customer data, we are perfectly positioned to build an intelligence layer that leverages this rich data source.

Your responsibilities will include working on complex problems such as:

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Senior Data Scientist - Test and Experiment

posted by: spj_bot

Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

As a Senior Data Scientist with strong expertise in graph theory and advanced data processing to join our Supply Chain Analytics team. The ideal candidate will have hands-on experience leveraging Python, PySpark, and graph-based approaches (preferably with NetworkX) to solve complex business problems in supply chain optimization.. You will develop efficient and accurate analytical models which mimic business decisions and incorporate those models into analytical data products and tools. You will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.

Key Responsibilities

Job Skills

color professional a b testing recommendation systems leadership managers marketers product managers calculations experimental design rate retention testable adobe target google optimize data scalable personalization storytelling automate r communication visualizations sql supply chain optimization customer journeys dashboards governance consultants translate analytical analytical skill graph career development python graph theory data processing conversion rate act bayesian modeling confidence interval communicate best practices data engineers analytics pyspark stakeholder management supply chain causal inference machine learn data science market research statistical analysis statistical modeling consulting randomization experimentation statistics sample size tests tests disability instrumentation machine learning validate economics tracking test integrity solve complex statistical e networkx data pipelines b optimizely google manage data manipulation
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Machine Learning Engineer (Recsys)

posted by: spj_bot

Machine Learning Engineer - Recommendation Systems

Location: London (Office)

Compensation: $250K - $300K

We are a high-growth software development company and a team of elite builders, known for our contributions to one of the largest crypto social networks globally. Our pioneering platform allows anyone to create a coin in under one minute for free, establishing itself as the home for memecoin creation and trading on Solana. The platform has generated over $700 million in revenue and is focused on building the future of social crypto. We are seeking a Machine Learning Engineer to build and scale our core recommendation systems.

You will be responsible for designing, building, and deploying the machine learning systems that drive user discovery and engagement across our rapidly growing platform. This is a high-impact role requiring end-to-end ownership of critical features, ensuring our models scale effectively to handle significant real-time volume and user activity.

Key Responsibilities:

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