Moises Baly
Verified Expert in Engineering
Machine Learning Developer
New York, NY, United States
Toptal member since August 8, 2016
Moises is a finance and strategy professional with a software engineering background. He is passionate about identifying opportunities in complex problems. Drawing on his two master's degrees and professional experience, he enjoys bridging the gaps between technical product knowledge, financial strategy, and general business acumen. Moises holds an MBA from the MIT Sloan School of Management and a master's in computer science from Cornell University.
Portfolio
Experience
- SQL - 6 years
- Java - 4 years
- Android - 4 years
- Scala - 2 years
- Python - 2 years
- PostgreSQL - 1 year
- Cassandra - 1 year
- Machine Learning - 1 year
Availability
Preferred Environment
Python
The most amazing...
...thing I've coded was a kernel density estimate function for spatial scoring of places based on distance.
Work Experience
Investment Banking Associate
Guggenheim
- Conducted rigorous financial analyses and company valuations, scrutinizing financial statements and industry research to support clients in navigating strategic M&A transactions within the TMT sector.
- Prepared business development materials and financial models to facilitate client presentations and communicate investment opportunities to potential investors.
- Managed and mentored junior team members, overseeing the delivery of high-quality work products while supporting their professional development.
Software Engineer
Bloomberg
- Led a team of engineers to enhance Bloomberg’s Quant platform (BQuant) by scaling its cloud computing capabilities. Defined technical roadmap, managed team priorities, and facilitated collaboration among stakeholders.
- Implemented Agile practices for a team of engineers, ensuring continuous delivery, effective stakeholder communication, and seamless partner onboarding.
- Provided technical consulting services to engineering teams, guiding them in navigating technical hurdles and facilitating the rollout of solutions tailored to their specific business requirements.
- Advocated for investment in Bloomberg's Quant platform big data initiative, leading to team growth while contributing to company-wide talent acquisition efforts through engineer recruitment and mentoring.
Product Engineer
Spatially
- Designed and implemented scalable/distributed spatial computation engines. As a member of the core engineering team, contributed to developing the spatial-aware infrastructure.
- Spearheaded the migration from a conventional spatial back-end infrastructure (PostgreSQL, PostGIS) to a NoSQL architecture sitting on top of technologies such as GeoWave, Cassandra, Spark, and others.
- Developed microservices for querying data sets counting millions of records.
- Scaled and productized the company's spatial research prototypes developed by our data scientists.
Software Engineer
ATOS Inc.
- Worked within ATOS e-payment services, specifically in a back-end project for financial entities and banks.
- Assisted the team leader with project time management. Prepared and delivered technical demos to distributed teams in India.
- Developed a web application for monitoring interbank movements of compensation and fraud.
Experience
Scientific Calculator and Simple Linear Equation Solver
The calculator is written in Scala using sbt. To run the project, at least Scala version 2.11.8 is required and sbt version 0.13.11.
2D Bin Packing Library for Irregular Pieces
https://github.com/mses-bly/2D-Bin-PackingThe 2D bin-packing problem consists of a given set of 2D pieces with unknown form or shape; we have to place them in a series of rectangular bins, minimizing the material used. In other words, we have to place all the pieces in as few bins as possible.
The problem is NP-hard, thus there is no guarantee that an algorithm will provide an optimal solution, although we can compare different solutions in terms of how many bins an algorithm has used for a particular set of pieces. This project tries a few heuristics and approximations to solve the problem with a reasonable amount of computational effort, given that a brute-force approach to the problem would take an infinite amount of time.
Android with Geolocation API Integration | Sample code
https://github.com/mses-bly/AndroPlacesWeka on Spark | Proof of Concept
https://github.com/mses-bly/WekaOnSparkEducation
Master's Degree in Business Administration
MIT Sloan School of Management - Cambridge, MA, USA
Master's Degree in Computer Science
Cornell University - Ithaca, New York, USA
Engineer's Degree in Computer Science
Polytechnic University of Valencia - Valencia, Spain
Skills
Libraries/APIs
Bloomberg API, Pandas, NumPy, Scikit-learn, Spark ML, JTS Topology Suite
Tools
Excel 2010, Microsoft PowerPoint, Amazon Elastic MapReduce (EMR), Git, GeoTools, Apache Maven, SBT, ScalaTest, IPython Notebook, PyCharm, IntelliJ IDEA, Spark SQL, Eclipse IDE
Languages
Scala, HTML, Python, Java, SQL, Go, CSS
Frameworks
Spark, Apache Spark, Play, Flask, JUnit, Hibernate, Apache Tapestry, Django REST Framework
Paradigms
Functional Programming, Spatial Databases, Object-relational Mapping (ORM), Scrum, Object-oriented Programming (OOP), Kanban
Platforms
Apache Kafka, Linux, Android, Java EE, Oracle, Windows
Storage
JSON, Oracle 11g, Cassandra, PostgreSQL, DB, MongoDB
Other
Finance, Technology, Software, Bloom Query Language (BQL), Machine Learning, Data Structures, GeoJSON, Strategy, Apache Cassandra, Computational Geometry, Spatial Statistics, Apache Accumulo
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