FreightFlows, Inc | Infrastructure Engineer | Remote, Boston MA USA
*Company*
FreightFlows is a fully remote, well-funded data and analytics startup based in Boston, MA. We track and predict ship movements and cargo flows for the 30,000 largest shipping vessels in the world, a $300bn industry. The world of global shipping is immense, unwieldy, and is in the early stages of undergoing a digital overhaul.
*Role*
FreightFlows is growing fast and we're looking for an infrastructure engineer to grow with us. This is a high impact position. You'll be responsible for building the infrastructure that powers our data science platform, and ensuring a seamless process for developers and data scientists.
Our stack includes AWS, Airflow, Spark, and Docker on ECS. We've just started exploring Terraform/CloudFormation, Kafka and possible Kubernetes for future projects a well.
*Requirements*
- Strong overall programming skills: able to write modular, maintainable code, preferably in Python
- Expertise building code-driven infrastructure on public cloud platforms (preferably AWS with Terraform or CloudFormation)
- Expertise building CI/CD pipelines
- Experience with Docker and Linux
- Experience with SQL
- Experience configuring and maintaining relational databases
# FreightFlows | Data Scientist / Sr Data Analyst / Data Engineer | Boston, MA USA | ONSITE or REMOTE | Full-time #
_What we do_
Maritime transportation accounts for nearly 4% of all global climate change emissions. 77% of tonnage moved on the water happens in bulk ships (ie tankers) and not container ships. These ships operate like taxis, and their idle time, and empty voyages reveal a very inefficient transportation system.
FreightFlows tracks every boat on the water in real-time and predicts what they'll do next. We leverage unique access to hundreds of millions of live data points/day to analyze and optimize seaborne bulk trade (such as oil, gas, chemicals, aggregates, ore and coal).
We're helping shippers and vessel operators to forecast freight partners, helping to secure favorable market pricing and reducing idle time and empty legs for ships.
Our goal is to significantly reduce the impact of climate change emissions in the maritime transportation industry by driving down the cost of trade and maximizing utilization.
_What we need_
We're a small but experienced team, with experience in maritime tech, commodity analytics and machine learning.
We are looking to add a colleague to our Analytics team, who will develop models and build the associated data pipelines to put them into production. This is an excellent opportunity for an engineer who wants to focus on data science or a data scientist who wants to focus more on software development. The team is small and you will have responsibility to create, test, and implement improvements from a roadmap you will help author.
You will learn the nuances of our AWS backend and will work on modeling -across structured historical vessel & port data, geospatial data, and scraped industry data- using primarily python and some SQL. You will be responsible for implementing client-facing databases and visualizations, and will need to stay up to date with various modeling research, as it pertains to our problem set. We are creating a unique solution in our industry, and we value creativity, dedication, and honest skepticism in our development teams. Our market is global and we welcome applicants from anywhere in the world; you will work remotely but must be available for some meetings in US Eastern time.
You are among the first hires after the founding team, so you need to be comfortable with an uncertain future, fast paced development, risk taking, and the excitement that comes with seeing real world problems fixed with what you do every day. Diverse applicants very welcome - if you think you can help, then please get in contact!
# FreightFlows (Currently MassChallenge 2020 cohort) | Sr. Data Engineer, Jr. Software Engineer | Boston, MA USA | ONSITE or REMOTE | Full-time #
_What we do_
Maritime transportation accounts for nearly 4% of all global climate change emissions. 77% of tonnage moved on the water happens in bulk ships (ie tankers) and not container ships. These ships operate like taxis, and their idle time, and empty voyages reveal a very inefficient transportation system.
FreightFlows tracks every boat on the water in real-time and predicts what they'll do next. We leverage unique access to hundreds of millions of live data points/day to analyze and optimize seaborne bulk trade (such as oil, gas, chemicals, aggregates, ore and coal).
We're helping shippers and vessel operators to forecast freight partners, helping to secure favorable market pricing and reducing idle time and empty legs for ships.
Our goal is to significantly reduce the impact of climate change emissions in the maritime transportation industry by driving down the cost of trade and maximizing utilization.
_What we need_
We're a small but experienced team, with experience in maritime tech, commodity analytics and machine learning.
Data Engineer: We need you to be a leader in developing the data processing and analytics pipeline. You need to have knowledge of python, experience with cloud architecture, big data, data structures, core data science algorithms and distributed systems. Ideally, you'll advise and steer the backend data development toward high availability, optimized processing and data delivery.
You are among the first hires after the founding team, so you need to be comfortable with an uncertain future, fast paced development, risk taking, and the excitement that comes with seeing real world problems fixed with what you do every day. Diverse applicants very welcome - if you think you can help, then please get in contact!
Essentially, all vessels over a certain tonnage are required to broadcast identification data (AIS) for safety regulation so other vessels can identify them. Many companies now exist that listen in on those public vessel broadcasts and aggregate the date. Messages are sent by the vessels constantly, and terrestrial antenna are installed by companies, or assisted by volunteer hosts to help collect the messages along coastlines. Satellite companies can aggregate as well, but are usually hindered by how often the pass over a certain area (10 minutes of visibility every 90 minutes, depending on the constellation, and the company).
All in, the larger AIS data aggregators collect about 500 million messages a day from around 150,000 vessels through terrestrial and satellite sources. Access to the full feed, with no delay, is sold for up to $500k/year, though typical deal sizes are around $75k/year. Access to online map-based products usually cost around $10k/year.
<== Used to work for one of the large AIS companies
>The system is based on the collection and processing of data transmitted via the AIS (Automatic Identification System). The AIS-Receiving stations that comprise the MarineTraffic network pick-up such data and share it with the MarineTraffic central database.
>All vessels equipped with an AIS transponder emit AIS-data which can be received by any AIS-receiving unit provided it is within range. AIS message packets are encoded in NMEA sentences (64-bit plain text). A sample is shown below:
>!AIVDM,1,1,,B,1INS<8@P001cnWFEdSmh00bT0000,0*38
>The contents of any incoming NMEA sentence can be decoded. This way, information on the following three basic sections can be deducted:
>Dynamic Information, such as the subject vessel’s position, speed, current status, course and rate of turn.
Static Information, such as the subject vessel’s name, IMO number, MMSI number, dimensions.
Voyage-specific Information, such as the subject vessel's destination, ETA and draught.
The central database constantly receives and processes large amounts of AIS-data and stores the most important part of it (together with geographic information on a multitude of ports and areas, vessels' photos and other details). Current positions and/or tracks of vessels are displayed on the MarineTraffic Live Map while Positions History, Vessel Details, Port Conditions and Statistics can be easily found using our dedicated web pages.
FreightFlows | Data/backend Engineer. Also Sales/Marketing and Product roles | Boston, MA USA | ONSITE or REMOTE
We're a new startup from Boston focused on the $20 Trillion dollar global seaborne trade market.
FreightFlows provides aggregated, predictive analytics for global trade. While maritime data continues to grow in volume and complexity, actionable insights continue to be elusive. The industry instead deals with inaccurate, stale and biased data from many fragmented sources. The complexity of bringing together trusted, timely information means companies have had to rely on dubious, incomplete market insight and therefore make decisions on anecdotal evidence. FreightFlows uses proprietary data science algorithms to synthesize data into trade truth, predictive analytics and actionable intelligence for traders, shippers, owners and brokers.
Ask me anything.. Matt Morgan, Founder hello@freightflows.com
FreightFlows | Data Engineer, Devops Engineer. Also Sales/Marketing and Product roles | Boston, MA USA | ONSITE or REMOTE
We're a new startup from Boston (< 6 months old) focused on the $20 Trillion dollar global seaborne trade market.
FreightFlows provides aggregated, predictive analytics for global trade. While maritime data continues to grow in volume and complexity, actionable insights continue to be elusive. The industry instead deals with inaccurate, stale and biased data from many fragmented sources. The complexity of bringing together trusted, timely information means companies have had to rely on dubious, incomplete market insight and therefore make decisions on anecdotal evidence. FreightFlows uses proprietary data science algorithms to synthesize data into trade truth, predictive analytics and actionable intelligence for traders, shippers, owners and brokers.
Ask me anything.. Matt Morgan, Founder hello@freightflows.com
How about taking a look at the voice talent to understand why the characters are largely male dominated? Dan Castellaneta, Hank Azaria and Harry Shearer account for the largest majority of characters on the show. They have incredible flexibility and range. Nancy Cartwright voices Bart (not accounted for in the male/female numbers) and several other male characters, and thus expands the male repertoire. Yeardley Smith (Lisa) and Julie Kavner (Marge) have pretty distinct voices, and while incredibly talented, don't contribute many more characters to the show outside of "soundalikes" like Marge's sisters, etc.
It's such an incredibly outdated way of conducting business. The podcast was really terrific in showing the underworkings of an industry that I would never even think twice about. Very interesting
Looks like normal operations after departing container berth. Concerning is the speed ramping up.