Jacob D. Reinhart Email & Phone Number

Chicago, Il, Us

San Francisco, Ca, Us

New York, Ny, Us

• Autonomous construction and risk management of a portfolio of energy and soft commodity, short-term interest rate, fixed income, equity index, and foreign exchange futures products and algorithmic & discretionary quantitative trading strategies.• Python script writing to generate and visualize probability distributions, descriptive statistics and other custom metrics of interest from large historical high-frequency (tick) datasets to optimize the deployment of working (risk) capital.• Write algorithms/pricing filters to uncover and exploit market inefficiencies by algorithmically arbitraging products which trade on multiple exchanges and/or in different currencies.• Employ time-series, linear regression and clustering analyses and other supervised/unsupervised machine learning techniques, in Python or Spark, to develop theoretical pricing and risk models. • Research and optimize new and legacy trading strategies/parameter settings by simulating and backtesting the strategies using self-built Python-based simulator, based on historical market data.• Optimize business processes and procedures to efficiently manage time, technological, and capital resources.• Problem solve and tackle technical issues arising from software and hardware by liaising with in-house IT, trading software vendors, and exchange representatives.

New York, Ny, Us

• Co-led team of data scientists tasked with thoroughly investigating, validating, and resolving Salesforce ticket-driven data inquiries submitted by the company’s host of fast-moving consumer goods (FMCG) clients.• Communicated detailed findings of data inquiry investigations and technical resolutions to Sales/Product leaders and their clients via Google Chat video presentations to ensure customers’ understanding of Nielsen’s data products and methodology.• Authored packages of custom functions and automated scripts in Python & SQL for data extraction, validation, analysis, and visualization to aid our team in addressing clients’ data inquiries, reducing time to deliver service level objectives by 25%.• Co-instructed weekly training sessions on building/replicating scalable tools for the data science team that facilitated migration of company’s legacy data science apparatus (written in SAS) towards open source technologies such as Python and Apache Spark, in a successful effort to help reduce company’s multimillion-dollar licensing costs.• Led exploratory data analysis and vetting of a third party’s driving/geospatial dataset and extracted meaningful insights about drivers’/consumers’ behavior and travel patterns to POIs, which included the universe of Nielsen’s FMCG clients’ locations.• Co-led research into methodologies for modeling higher frequency (daily) volumetric data extracted and "temporally disaggregated" from Nielsen's (legacy) weekly-frequency data product dissemination.

Leveraging the considerable knowledge and experience I have accrued over nearly a decade in the proprietary trading industry working as a Quant-Trader and Risk Manager, I provide strategic consultancy services to my clients/partners by conducting quantitative research on large datasets, by deriving actionable information from statistical learning models which I construct from that data, and by engineering cleverly crafted and robust execution algorithms to be used for the implementation of sophisticated trading and hedging strategies across global financial markets.My "Tech Stack" includes the following languages/technologies (listed in order of proficiency) and is of the format: Language | Packages, where relevant:• Python | numpy, pandas, sklearn, networkx, datetime, matplotlib, seaborn, bokeh, PyTorch...• SQL | MySQL, PySQL : Advanced query writing and efficient/non-redundant Schema design• Apache Spark | Spark SQL, PySpark : Very comfortable with wrangling structured & unstructured, numerical and textual, "Big Data" for inputting into the host of Machine Learning algorithms available via Spark's analytics engine, including but not limited to: Regression (OLS/Ridge/Lasso/Trees), solving Classification problems with Logistic Regression/Decision Trees/kNN/SVM/GBT/Bagging/Random Forests etc; Dimensionality reduction/feature selection techniques such as Feature Importance Scores, SVD, PCA; implementing Cross-Model-Validation/Hyperparameter tuning via Grid Search to determine the "best model"; and with using model output to articulate business insights and formulate strategy/road-map forward.• R | xts, zoo, lubridate, quantmod, ggplot2, MICE, rpart, PARTY, CARET, randomForest, e1071, kernLab...• AWS Boto3 | IAM, S3, SNS, Comprehend, Rekognition

• Built and operated a proprietary trading business within a physical energy commodities trading company, managing asset class/securities selection, risk modeling, strategy design and execution & risk mgmt, building and pitching a business plan and receiving buy-in from management and investors• Autonomous construction and risk management of a portfolio of energy and soft commodity, short-term interest rate, fixed income, equity index, and foreign exchange futures products and discretionary quantitative trading strategies• Python and R script writing to generate and visualize probability distributions, descriptive statistics and other custom metrics of interest from large historical datasets to optimize the deployment of working (risk) capital • Wrote business logic for, and authored cleverly crafted execution algorithms to fully automate trading strategies using Algorithm Design Lab (ADL)• Tracked, analyzed and disseminated data and information related to domestic and international export and import quantities, pipeline outages, refinery capacity utilization and run-rates, scheduled shutdowns and turnarounds, and estimated their effects on supply/demand balances and inventory levels, and used information to form a consensus market view to help guide group’s physical and financial trading and risk management decisions• Requested and beta tested new features to front-end trading execution software from and for software vendors• Optimized operating profit margin by identifying and improving upon inefficiencies in business processes and/or uses of capital and by negotiating more favorable exchange, clearing and commission fee structures with exchanges and FCMs to reduce transactions costs

Low, Medium, & High Frequency Quantitative & Discretionary Trading StrategiesAreas of Expertise/Products Traded:• Relative Value Arbitrage• Statistical Arbitrage• Inter-Exchange/Cross-Currency Arbitrage• Inter-Commodity Spread Arbitrage• Basis Arbitrage• Event Driven, Momentum-Based and Trend Following strategies• Short-Term Interest Rates (STIRs): Eurodollars, Euribor, Short Sterling, Euroswiss• NYMEX & ICE Energy Complex: WTI, Brent, NG, RBOB, Heating Oil & European Gasoil (ULSD)• CME/CBOT, ICE & Eurex: U.S., German, UK, & Italian Treasuries and Equity Indexes• ICE & NYSE LIFFE Softs: Cocoa, Sugar, Coffee, Cotton• CME FX: G10 Currencies & Cross-Rates• CME/Comex/LME: Precious and Base Metals: Gold, Silver, Platinum, Palladium, Copper

Chicago, Illinois, Us

• Engineered an automated trading system which deployed and managed proprietary market-making algorithms which supplied substantial liquidity (≥ 1MM contracts per annum) to the Dollar, Euro, Sterling, and Swiss Franc Short-Term Interest Rate (STIR) futures markets • Researched and developed quantitative trading strategies which utilized statistical & relative value arbitrage techniques to identify & capitalize upon arbitrage opportunities in energy and soft commodities futures markets• Discovered and exploited market inefficiencies by algorithmically arbitraging products which traded on multiple exchanges and/or in different currencies• Mitigated foreign exchange risk to non-native currency balances by hedging with FX futures • Employed time-series, linear regression and cointegration analyses in R to develop proprietary pricing and risk models • Leveraged R to compute descriptive statistics and generate probability distributions from large historical Reuters tick datasets• Researched and optimized new and legacy trading strategies by simulating and backtesting the strategies in R and CQG• Optimized business processes and procedures to efficiently manage time, technological, and capital resources• Problem solved and tackled technical issues arising from software and hardware by liaising with in-house IT, trading software vendors, and exchange representatives

• Made electronic markets in U.S. Treasury cash bonds and futures during the Asian, European, and North American market sessions• Managed a complex portfolio of yield curve positions across six traders’ separate accounts using Chopper’s industry leading proprietary auto-spreader technology• Identified arbitrage opportunities between BrokerTech and eSpeed markets and manually legged into or out of spreads to take profits or capture edge• Analyzed charts of spreads and outrights and employed technical analysis to identify trends, support & resistance levels, and high risk-reward trading setups• Brainstormed with team of trader colleagues in an effort to modify strategy to best manage the group’s risk upon the release of new information and in situations of high market volatility• Researched, developed and designed new strategies for spreading Equity Index and Commodity futures then tested, implemented and traded these new strategies• Engineered automated Microsoft Excel spreadsheets that used real-time data to calculate spread values, plot and chart live data, and track traders’ position P&L • Trained a new team member on all operational procedures and taught him how to trade our strategies• Setup and maintained traders’ trading stations, made all necessary changes to systems settings, and troubleshot and resolved any issues with IT

New York, Ny, Us

• Assisted traders in all matters related to our Designated Primary Market Maker (DPM) trading floor market-making operations • Operated four “greybox” trading machines which streamed continuous electronic quotes on four exchanges (CBOE, PHLX, AMEX, BOX) for 250+ standardized and OTC Equity and ETF options and swaptions (CDS) products• Programmed automatic quoting logic for streaming electronic quotes and responding to various electronic special order types• Set and modified all pricing inputs including implied volatility, skew, kurtosis, interest rate, dividend amount and ex-dividend dates being priced into our options’ theoretical fair values• Continuously scanned portfolio of products for pricing inefficiencies, potential arbitrages, inter- and intra- product relative value opportunities (skew and volatility) and favorable risk/reward opportunities and shared this information with team • Utilized Microsoft Excel, VBA, and Bloomberg DDE links to build and automate spreadsheets which tracked underlying assets’: historical volatility, correlations to benchmarks and other underlying assets, closing prices, and dividends, earnings, and corporate actions declarations• Maintained spreadsheets that bootstrapped the yield curve, tracked the risk-based haircut charges for each options series, tabulated portfolio’s Greeks exposure and mark-to-market P&L• Participated and excelled in classes on options pricing theory and mock trading exercises

• Supported the fund accounting / fund solutions group in preparing for the year-end audit• Used Income Statement and Balance Sheet components to calculate the Net Asset Value (NAV) for 90+ hedge fund portfolios• Reconciled fixed income, equity, and derivative securities' positions with respect to quantity, cost, MV, and P&L to third party admin • Calculated accruals of both asset and performance based fees due to hedge fund managers

Chicago, Il, Us

• Forecasted future fee obligations based on statistical analysis of portfolio assets' growth using nïave Bayes• Calculated funds' tracking error and tracking risk using performance data from Markov Processes International (MPI) • Created quantile rankings of our 16 sub-advisers by fee structure and commission recapture programs • Produced performance presentation materials in the form of charted periodic performance data for all 96 funds under administration• Designed worksheets which allocated accrued asset-based fees across 96 funds under administration• Constructed, automated, and maintained VBA macro-driven MS Excel spreadsheets that tracked portfolio NAVs, performance and capital stock activity• Reconciled trades and capital stock movements for five funds daily

Us

• Gathered clients' daily trading activity from prime brokers' systems• Utilized Bloomberg terminals for the collection of all necessary data related to clients' portfolio holdings• Built MS Excel spreadsheets which imported data from Bloomberg then exported data to firm's proprietary portfolio accounting system via .txt files, via self-authored VBA macros• Analyzed financial statements from hedge fund client and clients’ prime broker / custodian, and reconciled them to own data in portfolio accounting system• Identified discrepancies in financial statements and input adjusting journal entries to resolve them• Input cash equity, fixed-income, equity and credit default swaps, contracts-for-differences, forwards, futures, and options trades into portfolio accounting system

Post Graduate Diploma, Data Science

Certificate, Applied Machine Learning

Post Graduate Diploma, Machine Learning & Artificial Intelligence

Bachelor Of Science, Economics

Bachelor Of Science, Finance