Benjamin Pachter

Contact Information

About Me

Hey there! Welcome to my corner of the internet where I get to share tidbits of my journey as a Quantitative Data Scientist. I am currently looking for a new team to channel my energy into, so if you are hiring, thank you for being here! If you have already gone through my resume, you won’t find anything new below other than a comprehensive list of technologies I am skilled in. Instead, I would direct you to check out the ‘Skillset’ page and other pages where I provide deeper insights into my experience and some basic demonstrations!

I’m just a passionate professional who thrives on helping business owners and employees streamline their everyday activities and process flows. Turning raw data into valuable insights is exhilarating to me (when it works)! Whether it’s through sophisticated statistical models, AI algorithms, financial engineering, or distributed systems, I love making sense out of datasets of all kinds.

Using tools like Python, R, C++, JavaScript, Power Query, SAS, and SQL, I reguarly tackle complex challenges head-on to uncover new trends and patterns that significantly influence valuable business decision-making. I integrate cutting-edge AI and machine learning techniques, including deep learning neural networks, to generate predictive insights. Additionally, I leverage distributed systems and blockchain technologies to build scalable, secure, and efficient solutions that redefine operational efficiency.

My expertise spans advanced financial engineering, using models like Black-Scholes for options pricing and Monte Carlo simulations for risk assessment. I also employ AI-driven algorithms for asset selection, credit scoring, and customer segmentation. By combining my knowledge of Apache Kafka, Spark, Hadoop, and other distributed technologies, I ensure real-time data processing and analytics.

Ultimately, my purpose is to harness the power of data and frontline technologies to drive innovation and operational efficiency, creating stress-free, insightful experiences for business owners and employees alike.

Skillset

Data Analytics & Visualization:

  • Strong expertise in advanced Excel modeling, Power Query, Power BI, and Alteryx for data augmentation, modeling and interactive dashboard development.
  • Skilled in SQL, DAX, and M scripting for ETL data manipulation.
  • Other technologies I am familiar with include Salesforce, Tableau, Dynamics 365, Apache Spark, Airflow, Kafka, Storm, Hadoop, Cassandra, NiFi, Hive, Google BigQuery, Amazon Redshift, Azure Synapse, Matplotlib, Seaborn, Plotly, etc. But this list is always growing!

Database & Cloud Server Management:

  • Proficient in SSMS SQL, Salesforce Dev (SOQL, Apex, and Flow Automations), Snowflake, AWS, Google Cloud, Azure services, MySQL, MongoDB, Cassandra, Azure SQL Database, Azure Cosmos DB, Azure Data Factory, Google Cloud Storage, Google Dataflow, Amazon RDS, Amazon DynamoDB, AWS Lambda.
  • Managed real-time data streams and processing using Apache Kafka, Spark Streaming, Apache Flink, AWS Kinesis, Apache HBase with Hadoop, and Google Cloud Pub/Sub.

Programming:

  • Python, SAS, R, Apex, JavaScript, Java, C++, C#, SQL, Go, Scala, MQ4/MQ5, Rust, Solidit Pine, Ruby, PHP, Swift, MATLAB, HTML, CSS, XML, VBA, DAX/M, Bash, PowerShell.
  • Skilled in using Python libraries such as Pandas, NumPy, SciPy, QuantLib, SASsession, ib_insync, PySpark, PyArrow, PyKafka, PyHive, Airflow, Cassandra, Dask, fredapi, Scikit-learn, XGBoost, TensorFlow, PyTorch, Keras, Django, Flask, tqdm, statsmodels, FastAPI, SQLAlchemy, and many more.

Investment Deal Making:

  • Adept in modeling and underwriting CRE lending deals (senior, mezz, preferred equity, JV) and performing asset-credit diligence.
  • Proficency in regression, classification, clustering algorithms for asset selection, credit scoring, logistics pattern identification, customer segmentation, and CRE asset KPI prediction.
  • Experienced in portfolio optimization, resource allocation, time series analysis, ensemble methods, dimensionality reduction, model evaluation, and hyperparameter tuning.

Distributed Systems & Blockchain:

  • Experience in designing distributed systems using Rust, Solidity, Hyperledger Fabric, Apache Kafka, Spark Streaming, Apache Flink, Hadoop, and others for large-scale data processing and real-time analytics.
  • Proficient in implementing blockchain solutions for secure and decentralized data management using technologies such as Ethereum, Hyperledger, and smart contracts.
  • Skilled in leveraging cloud platforms like AWS, Google Cloud, and Azure for deploying scalable and fault-tolerant distributed systems.
  • Experience in developing decentralized applications (dApps) using Solidity, Web3.js, Truffle framework, and Rust for blockchain programming.
  • Adept in using consensus algorithms, cryptographic techniques, and distributed ledger technologies to ensure data integrity, security, and transparency.

Strategic Business Understanding:

  • Investment strategy optimization, proactive risk management, micro-investment opportunity identification, quantitative data science.

Additional SaaS & Programming:

  • HubSpot, Dynamics 365, GitHub, SAP S/4 HANA, Pine, Bloomberg, Oracle.
  • Proficient in using various cloud platforms and technologies for ETL processes and real-time data integration.



Professional Experience

NYMT

New York Mortgage Trust

Acquisitions Analyst
Charlotte, NC
Jan 2022 – May 2024

  • Developed multifamily market/property investment tools with Python, Power BI, JavaScript, R, SQL, and Excel for analyzing Yardi Matrix, RealPage, FRED, FDIC, and Census data to identify high-potential investment opportunities and factor risks.

  • Supported and created underwriting, portfolio, and monte-carlo models leveraging Python, SQL, R, and other technologies to enhance strategic rate scenario analysis and investment selection.

  • Oversaw and architected scalable database solutions in SSMS SQL Server through stored prodecures to optimize legacy Excel-based process models, enhancing multi-team connectivity for cross-functional team-wide data handling.

  • Enhanced business processes through Salesforce system administration with Apex and Flow Automations, ensuring data consistency and automating key processes for Acquisitions and Asset Management teams.

  • Implemented advanced prediction models using scikit-learn, XGBoost, TensorFlow, etc. to refine property valuations for underwriting agency loans and to predict asset rent prices using time series data

  • Monitored and reported on macroeconomic developments via customized financial health indicators using public APIs for exposure risk assessment.

  • Conducted comparative statistical analysis with R and Python to evaluate asset performance against market benchmarks, employing NumPy, Pandas, and statsmodels for quantitative research.

  • Utilized C++ for high-performance computing tasks related to big data movement and analysis, integrating with SQL/Apache technologies for distributed big data processing through Azure cloud systems.

  • Provided macroeconomic risk analysis to the executive team, leveraging advanced data visualization tools like Power BI, Tableau, and Matplotlib for insightful presentations, and researched blockchain technologies to incorporate within the company’s strategy to remain on the frontines of tech capabilities.

Deloitte

Deloitte

Risk and Financial Advisory Analyst
Seattle, WA
Jan 2020 – Jan 2022

  • Streamlined client ETL workflows by integrating Python, SAS, SQL, Alteryx, AWS, and Apache technologies for an automated suite of combined technologies for maximum efficiency in financial, defense, and logistics data augmentation processes for financial risk assessment.

  • Developed advanced ML models/algorithms for clients using Python libraries and SAS to forecast client portfolio risks associated with interest rate hikes and bond volatility such as random forests, gradient boosting, ARIMA, GARCH, LSTM networks, and Monte Carlo simulations to enhance predictive accuracy.

  • Implemented distributed systems and blockchain solutions using Rust, Solidity, and Hyperledger Fabric for secure and efficient financial transactions and smart contract development.

  • Utilized neural networks in conjunction with LLM/NLP techniques to develop sentiment analysis tools for predicting market movements and product growth based on the analysis of social media and news feeds.

  • Optimized Black-Scholes options pricing models using QuantLib, NumPy, SciPy, and MQ4 in combination with Python, C++, and JavaScript.

  • Implemented lean logistical processes using SQL, Python, C++, JavaScript, and Apache technologies to optimize client CRM reliance for transportation logistics.

  • Modeled financial data for ERP migrations using SAP S/4 HANA and Azure/SQL for clients in e-commerce, transportation, and banking sectors.

  • Created interactive data dashboards with SAP S/4, Microsoft Dynamics, and Power BI for logistics and data monitoring.

  • Assisted clients in database migrations (SAP ECC to S/4 HANA & CFIN, Excel to Azure/SQL), ensuring seamless transitions and data integrity.

  • Established a global Chart-of-Accounts for consistent international financial reporting.

  • Coordinated data mapping for Customer Information Models with external contractors.

  • Developed commercial real estate analysis reports using Python, R, and Power BI, providing insights and trend forecasts.

  • Led transformation initiatives to transition from legacy Microsoft suites to Power Query/SQL.

  • Provided strategic guidance on Federal Reserve decisions and economic data trends.

  • Enhanced and developed Black-Scholes pricing models by integrating C++/R/Python for high-performance computations and JavaScript for interactive visualizations.

  • Employed Keras and TensorFlow for deep learning applications in financial risk modeling and predictive analytics.

  • Developed scalable data pipelines using Apache Spark and Kafka for real-time data processing and analytics.

  • Conducted backtesting and validation of financial models using historical data with Python, C++, and R.

  • Developed comprehensive documentation and user guides for financial models and tools, ensuring ease of use and accessibility for clients.

BMW

BMW Manufacturing

Supply Chain Planning Co-op
Greer, SC
May 2018 – Dec 2018

  • Led a major initiative to restructure supplier reorder processes with integrated SAS and Alteryx ETL automations, utilizing statistical analysis and predictive modeling of supply chain data and reducing transportation expenses by ~ $13 million per vehicle model.

  • Managed daily supply chain operations with Microsoft Dynamics 365 and SAP S/4, focusing on materials flow, packaging, and transportation.

  • Created interactive data dashboards with Power BI and Tableau for real-time supply chain monitoring.

  • Executed data mining and predictive analytics with Python and Excel modeling to support planners in integrating new logistics operations for BMW G05 X5, G06 X6, G07 X7, and G09 XM models.

  • Developed proactive machine learning models to forecast chain disruptions using Python, SAS, and C++.

  • Implemented new SQL and Apache technologies for supplemental data processing and analysis.

  • Automated client data augmentation workflows with Bash and PowerShell.

Education

University of North Carolina at Charlotte
BSBA Operations and Supply Chain Management & Management Information Systems
3.52 GPA
Aug 2015 – Dec 2019

Certifications (Coursera)

SAS Statistical Business Analyst

Hypothesis Testing Cred ID: NNX5EBR8RJAS
Jun 2024

Regression Modeling Fundamentals Cred ID: YTJSYGEC8JQ5
Jun 2024

Predictive Modeling with Logistic Regression Cred ID: 7CR4ZZHA5U4R
Jun 2024

Deeplearning.AI & Stanford Online**

Unsupervised Learning, Recommenders, Reinforcement Learning Cred ID: TG577TSS94PL8
Apr 2024

Advanced Learning Algorithms
Cred ID: VECYVW4GGGURA
Mar 2024

Supervised Machine Learning: Regression and Classification
Cred ID: 78MQGUZJIT8G
Feb 2024

Military

United States Army
MOS: 19K -> 35F
ROTC -> Active National Guard -> Active Army
General early discharge from service due to DoD Instruction 6130.03 Section 6.12
Mar 2015 – Mar 2018

Personal Life

Outside of my professional life, I dedicate my time to researching complex options trading strategies, focusing on automating brokerage APIs with machine learning concepts. I actively contribute to online forums like Discord, where I teach retail traders how to apply risk management and discipline to achieve financial independence through options and futures strategies. I also thoroughly enjoy reading whenever I get the chance. The subjects I am most interested in are current and historical economics/geopolitics, code developing, business & trading psychology, and evolutionary biology. When I’m not immersed in these activities, I enjoy spending time with my loving fiancé and our three cats in our cozy apartment. I also love mountain overlanding, hiking, exploring new local hangout spots - anything that feels like an adventure!

Thank you for being here, and remember, Thanks!