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Adjunct Lecturer from The London School of Economics
Neil A.

5.0 (82 ratings)

237 hours tutoring

Your first lesson is backed by our Good Fit Guarantee
Hourly Rate: $88
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Response time: 18 minutes

About Neil

Bio

I'm a seasoned analyst and adjunct lecturer with three years of teaching experience at the London School of Economics & Political Science. Throughout my career, I've provided statistical and programming expertise across various public-sector projects. In my role as an analyst, I developed price forecasts for domestic oil and petroleum products, applying principles from macroeconomics and statistics to link supply-demand dynamics with future projections. As a data scientist, I crafted...

I'm a seasoned analyst and adjunct lecturer with three years of teaching experience at the London School of Economics & Political Science. Throughout my career, I've provided statistical and programming expertise across various public-sector projects. In my role as an analyst, I developed price forecasts for domestic oil and petroleum products, applying principles from macroeconomics and statistics to link supply-demand dynamics with future projections. As a data scientist, I crafted innovative time series regression models to forecast aviation ridership demand, effectively using historical data to inform future trends.

As a lecturer, I routinely teach classes of 10-15 students, where I emphasize real-world applications to bridge theoretical concepts in statistics, econometrics, applied mathematics, and data science. I believe that relating practical examples to theory is key to fostering students’ understanding and engagement.

My teaching experience includes serving as a tutor and teaching assistant from 2014 to 2016, where I co-instructed Chemical Process Development at UMBC and privately tutored diverse mathematics levels, from elementary concepts to advanced Kaggle/Olympiad-style challenges. My classes attract a variety of students, but I specialize in teaching high school and college students core topics in statistics, calculus, and data science.

Additionally, I provide microconsulting services in statistics, machine learning, data science, and programming. This consulting work involves delivering targeted, actionable insights and custom solutions, empowering clients to leverage data-driven decision-making efficiently without requiring extensive engagements.

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Education

University of Maryland Baltimore County
Mathematics
University of Maryland Baltimore County
Masters

Policies

  • Hourly Rate: $88
  • Rate details: Preparation may be billed at standard rate based on lesson complexity. Short-notice lessons are billed at 1.5× the normal rate. Cancellations are charged after a 20-minute wait. Lessons start on time.
  • Lesson cancellation: 12 hours notice required

  • Background check passed on 9/2/2024

  • Your first lesson is backed by our Good Fit Guarantee

Schedule

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Approved Subjects

Calculus

Calculus

I have taught calculus as part of advanced-level math and statistics courses at both UMBC and the London School of Economics. My degrees in mathematics and chemical engineering required calculus at every level, from limits and derivatives through multivariable and vector calculus. I regularly used these tools in real engineering and statistical work, so I can show students why the concepts matter, not just how to solve the problems. My teaching focuses on building intuition alongside the mechanics.
Chemical Engineering

Chemical Engineering

I hold both a BS and MS in Chemical Engineering from UMBC, graduating with a 3.94 GPA. I have worked across several chemical industries, including pharmaceuticals and materials, applying core engineering principles to real production and process challenges. I also do energy forecasting for the federal government, using quantitative modelling to predict energy trends. This combination of strong academic training and hands-on industry and government experience lets me connect the theory to how it actually works in practice.
Computer Programming

Computer Programming

I teach and program across three major languages: R, Python, and MATLAB. My mathematics degree required extensive coding, and I taught programming to university students, guiding them through hands-on data analysis and computation. I used MATLAB heavily for graduate-level work in chemical engineering, applying it to numerical methods, modelling, and simulation of real engineering problems. This blend of teaching experience and advanced technical use means I can explain both the fundamentals and how these tools solve practical problems.
Data Analysis

Data Analysis

I am a Data Scientist with experience at the FDIC, FAA, and Department of Energy, where I build predictive models, perform data cleaning, and analyze large datasets using Python, RStudio, and Excel. I also teach university-level courses in Data Science (MN2196) and Business Analytics (ST2187), emphasizing statistical analysis, regression, and data visualization using tools like Tableau and R. My professional work includes regulatory risk modeling, econometrics, and real-world business intelligence. I specialize in helping students and professionals apply data analysis concepts to solve practical problems with confidence.
Data Science

Data Science

I have extensive experience as a Data Scientist and Operations Research Analyst, working for multiple government agencies including the FAA and Department of Energy. I regularly use Python and RStudio to develop predictive models, analyze large datasets, and implement machine learning algorithms. Additionally, I serve as an Adjunct Lecturer, where I teach Data Science (MN2196) and Business Analytics (ST2187), focusing on regression analysis, predictive modeling, and data visualization using tools like Tableau and RStudio.
Interview Prep

Interview Prep

I have coached job candidates on interview preparation as part of seminars, helping them present their skills clearly and confidently. I have reviewed resumes for private-sector roles, so I understand what hiring managers look for. My experience spans the full process, from tightening a resume to practicing answers for tough interview questions. I focus on practical, real-world advice that helps candidates stand out and land the role.
Machine Learning/ AI

Machine Learning/ AI

I routinely apply machine learning in my work as a Data Scientist at the FDIC and previously at the FAA and Department of Energy. I specialize in supervised learning methods including XGBoost, decision trees, ridge/lasso regression, and logistic regression, with applications in forecasting, classification, and anomaly detection. I teach Business Analytics and Data Science at the university level, where I guide students through model building, tuning, and evaluation using Python and R. Whether you're tackling a homework assignment or building a predictive model, I focus on clarity, intuition, and hands-on application.
Probability

Probability

I have taught probability theory as part of ST2187 and MN2196 at the London School of Economics, covering the core ideas students need for statistical modelling and prediction. As a statistician at a federal financial regulatory agency, I apply probability every day to real data problems, from distributions and expected values to uncertainty and risk. My mathematics degree gave me a deep theoretical grounding, so I can connect the formulas to what they actually mean. I focus on building real intuition for how probability works, not just memorizing rules.
Python

Python

I use Python daily as a statistician at a federal financial regulatory agency, where I build data analysis tools and internal Python packages to solve real regulatory problems. My mathematics degree relied heavily on Python for computation, statistics, and modelling. I have also taught Python to university students, walking them through hands-on data analysis and practical coding. This mix of professional development work and teaching means I can explain both how to write clean code and how to apply it to real-world problems.
R

R

I have programmed extensively in R throughout my mathematics degree, applying it across numerous courses in statistics, computation, and applied math. I taught R at the London School of Economics for MN2196 (Business Analytics, Applied Modelling and Prediction) and ST2187 (Business Analytics, Applied Modelling and Prediction), guiding students through data analysis and statistical modelling. My experience spans both writing R code for coursework and instructing others in its practical use.
Statistics

Statistics

I work as a statistician at various federal regulatory agencies, where I apply statistical and data analysis methods to real-world regulatory problems. My mathematics degree gave me a strong foundation in statistical theory, from probability and inference to regression and modelling. I taught statistics at the London School of Economics in MN2196 and ST2187, helping students master applied statistical modelling and prediction. This mix of hands-on professional practice and university-level teaching lets me explain both the theory and its real-world use.
Algebra 1
Algebra 2
Differential Equations
Finance
GED
GRE
SAT Math

Examples of Expertise

Neil has provided examples of their subject expertise by answering 2 questions submitted by students on Wyzant’s Ask an Expert.

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Neil A.'s Photo

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Ratings and Reviews

Rating

5.0 (82 ratings)
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Reviews

Extremely Knowledgable and Supportive Tutor

Neil helped me a lot while I was in the process of writing my research paper, teaching me about statistical techniques including OLS, GLS and autoregression, hypothesis testing, regularized regression (Lasso and Ridge), cross validation, the effects of multicollinearity, and principal component analysis in a way that was easy to understand especially since I didn’t have much prior knowledge in statistics and data science beforehand. He explained in detail different types of data including time series as well as which approaches would work best and what the pros and cons were for each. Neil is very knowledgable in his field and it was obvious that he genuinely cared about the success of my paper and whether I learned something, helping me troubleshoot and take different approaches with short notice all while explaining clearly why we were doing each thing. If I could give him more than 5 stars, I would since Neil deserves much more than that and his guidance was a huge help throughout and helped me take my project to the next level.

Carmen, 52 lessons with Neil

Extremely knowledgeable and clear in his instruction

Neil reviewed my daughter's economics paper. He provided logical guidance, pointed to additional research, and prescriptive instruction on how to strengthen her paper. He is extremely knowledgeable about modern economics, and his feedback is clear. I highly recommend him!

Mona, 4 lessons with Neil

Exceptional Graduate-Level Statistics & R Support

I had five sessions with Neil for graduate-level statistics support in R, and he was a huge help. He’s very quick to respond, and quickly understood what I needed support with. He explains things clearly, adapting the sessions to my specific questions rather than following a fixed script. I really appreciated how he cared about both my progress and my understanding. I’d highly recommend Neil to anyone looking for reliable, thoughtful statistics tutoring.

Yavor, 5 lessons with Neil

Statistics

Neil is a great instructor and a master of the material. He uses creative techniques to ensure that you learn the fundamentals of statistics in addition to advanced statistical theory. Highly recommended!

Bryan, 70 lessons with Neil

Great tutor

Neil is working with me on extremely complex math problems and is showing up prepared for every meeting, helping me learn these advanced concepts at my own pace. I highly recommend him!

Yoav, 5 lessons with Neil

Highly Recommend! Very Knowledgeable and Easy to understand!

Neil is exceptional! He was very knowledgeable and patient. He took the time to review my daughter’s presentation before they met and gave her invaluable input. He walked her through how to approach the data and think critically, which enhanced her understanding. He gave great insight on the presentation and really helped her to visualize the data. He provided great guidance and assistance. Neil brings a calm and surety to his tutoring sessions and was a huge help. Highly recommended A+++ tutor!

Patty, 2 lessons with Neil

Knowledgeable, patient tutor

Neil was fantastic and very knowledgeable! He took the time to walk me through every question I had and made sure I truly understood each concept. Thanks to his clear explanations, patience, and guidance, I finally felt confident and understood the material by the end of our session.

Saba, 6 lessons with Neil

Amazing Feedback

Neil recently reviewed a Powerpoint I sent him and he gave an amazing and details analysis of it, with some very helpful insights. He went above and beyond for the scope of what I asked.

Connor, 7 lessons with Neil

Very knowledgeable and prepared tutor

I tutored with Neil regarding time series analysis on a time series dataset to predict monthly reservations. Neil went into depth about how and why we could use different approaches like PACF, ACF, differencing, ARIMA, PDARIMA, GARCH, ARCH, Exponential smoothing, and more. He explained the pros and cons of each models, and also helped me code the entire model with explanations on the parameters. He is knowledagble about statistics in general too which is a requirement for time series analysis. Data science can get confusing and often needs a lot of iterations. Some tutors online are irresponsible of their work, where they won't care if their output/response is wrong but Neil takes responsibility for the quality of the work he is providing. Not only does he prepare beforehand but is also honest about what works and what does not and how to improve things given the short deadline.

Youngbin, 5 lessons with Neil
Hourly Rate: $88
Response time: 18 minutes
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