7 days ago
To solve climate change, wealth inequality, supply chain stability, and national security we must change how our global supply chains work. Altana is a Trusted Commerce Platform built on a shared source of truth for the global supply chain. The purpose of Altana is to enable resilient, sustainable, secure, and inclusive global commerce: Globalization 2.0.
We have built a layer of shared intelligence across the world’s supply chain information: a living map of trillions of dollars of B2B commercial activity, covering 400M companies connected by billions of shipments. This knowledge graph powers Altana’s Trusted Commerce Platform - the Altana Atlas - which, after only three years since founding, is already used by many of the world’s most important governments, enterprises, and logistics providers.
Our product suite enables our customers to gain unprecedented visibility, benefit from shared artificial intelligence across a federated network of data, and interact across the network through a shared source of truth. We help our customers to build and manage trusted global supply chains.
The Financial Services team is looking for talented Financial Engineers to help execute this vision. You’ll work closely with our Clients, Data Scientists, Product Managers, Software Engineers, and leadership team to deliver quantitative insights that facilitate informed management of financial risks and opportunities related to supplier networks and global trade.
- Work with clients, software engineers, data scientists, solutions managers, and business development teams to develop models and simulations of financial risk in supplier networks
- Provide descriptive, predictive and prescriptive guidance on financial risks to businesses and their supplier networks
- Generate insights through predictive scoring, simulation, causal analysis, and other relevant modeling approaches to support tactical and strategic decisions about financial risk management
- Create probabilistic models of low frequency, high severity events and deliver them in the context required for supporting business decisions
- Use time-based system analysis and forecasting to understand past performance and estimate potential outcomes under a range of scenarios
- Identify risk profiles and their relationships to factors that contribute to risk
- Deliver solutions for portfolio optimization based on risk tolerance
- BS, MS, or PhD degree in Quantitative Finance, Statistics, Operations Research, Applied Math, or equivalent experience
- You have experience delivering predictive scoring models and scenario-based portfolio simulations in support of business decisions
- You enjoy helping people understand how models work
- You are excited by opportunities to build probabilistic models
- You are comfortable communicating technical analysis to less technical stakeholders
- You believe Thinking in Systems should be part of every primary school curriculum
- You are interested in using modeling and simulation to improve the world
- You have strong written and verbal communication skills
Nice to have, but not required
- Experience with Apache Spark, Databricks
- Experience with catastrophe or other extreme event modeling
- Experience with probabilistic programming and active inference
Technologies we love
- Languages: Python, Spark, SQL
- Tools: Scikit-learn, Numpy, Pandas, Numpyro, PyTorch, Tensorflow, CadCAD
- Datastores: Databricks, Elasticsearch, Postgres, RDS, Kafka
Why it’s great to work at Altana
- We love to collaborate, and we win as a team!
- We are committed to engineering excellence
- We value personal and professional development
- We learn from diverse backgrounds and perspectives
- We impact the world, from enabling developing countries to identifying drug traffickers
Altana is an equal opportunity employer with a commitment to inclusion across race and ethnicity, gender, sexual orientation, age, religion, physical ability, veteran status, and national origin. We offer a comprehensive healthcare package and paid parental leave of 3 months for the primary caregiver and 1 month for the secondary caregiver.
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