Victor Davis, Data Science Developer in Atlanta, GA, United States
Victor Davis

Data Science Developer in Atlanta, GA, United States

Member since October 3, 2017
Victor is an AWS-certified back-end developer and data scientist with over ten years of experience, passionate about the overlap of math, data, and language. Intellectually curious, quick to master new concepts, and always hungry for a challenge, he has excellent written and verbal communication skills and strong leadership, consulting, and public speaking abilities. Victor is a lifelong learner who strongly believes in ongoing education, travel, and work-life balance.
Victor is now available for hire

Portfolio

  • Toptal Clients
    Statistics, Machine Learning, Data Analysis, SQL, R, Python, Flask, APIs...
  • Boaz Media Network Solutions
    SSRS, Microsoft Dynamics, Global, Microsoft SQL Server, Microsoft Access, SQL...
  • Waffle House
    KML, MySQL, PHP, JavaScript, .NET, C#, SQL Server Integration Services (SSIS)...

Experience

Location

Atlanta, GA, United States

Availability

Part-time

Preferred Environment

GitHub, SQL, Linux, Python, Amazon Web Services (AWS), Analytics, Back-end, Git, JSON, Databases

The most amazing...

...discovery I've ever published is a novel formula describing the type-token relation which outperforms Heaps' Law.

Employment

  • Data Scientist

    2018 - PRESENT
    Toptal Clients
    • Acted as the principal developer of the Data Analytics library for a fintech startup building, validating, and monitoring financial models (Python). [Brussels, BE].
    • Served as a Back-end developer and data scientist contributing to a B2B Marketing SaaS product (Python). [London, UK].
    • Presented talks at trade conferences and published in trade journals. [New York, US].
    • Created data visualization software for pediatric doctors to share diagnosis and treatment information across centers using R. [Santiago, CL].
    • Served as a corporate trainer teaching the R, a programming language. [Seattle, US].
    • Tested and optimized code for hotel pricing software using R. [Brussels, BE].
    Technologies: Statistics, Machine Learning, Data Analysis, SQL, R, Python, Flask, APIs, Artificial Intelligence (AI), Data Analytics, Statistical Analysis, Pandas, NumPy, Data Science, RStudio, Predictive Modeling, Predictive Analytics, Natural Language Processing (NLP), Text Analytics, Clustering, Linear Regression, Logistic Regression, Statistical Modeling, Model Validation, Monte Carlo Simulations, Markov Chain Monte Carlo (MCMC) Algorithms, Monte Carlo, Scikit-learn, Jupyter Notebook, RStudio Shiny, Data Queries, Object-relational Mapping (ORM), Bash, Bash Script, Unit Testing, JSON Web Tokens (JWT), API Development, REST, Test-driven Development (TDD), Docker, Financial Modeling, REST APIs, Amazon EC2 (Amazon Elastic Compute Cloud), GitHub, Data Analyst, Redshift, Analytics, Transact-SQL, PHP, JavaScript, HTML, CSS, Data Modeling, Data Visualization, Back-end, Object-oriented Programming (OOP), Git, JSON, Fintech, API Integration, Databases
  • IT Consultant

    2014 - 2018
    Boaz Media Network Solutions
    • Supported operators in inventory control, BOM and router management, material ordering, and logistical optimization.
    • Created BI dashboards and KPI scorecards communicating floor metrics to the C-level.
    • Wrote reports using Crystal and SSRS for all the departments.
    • Generated performance metrics through complex data mining and SQL data wrangling.
    • Developed software and analytical tools for miscellaneous clients.
    Technologies: SSRS, Microsoft Dynamics, Global, Microsoft SQL Server, Microsoft Access, SQL, R, Crystal Reports, Data Analytics, RStudio, Microsoft Excel, ETL, Bash, Bash Script, Data Analyst, Analytics, API Integration, Databases
  • Software Developer

    2010 - 2014
    Waffle House
    • Created interactive Google Maps using JavaScript, KML, and mathematical functions.
    • Implemented mathematical algorithms in COBOL to boost processing speed.
    • Generated BI reports based on analytical insights using SQL and R.
    • Wrote adapters for getting multi-generation platforms to communicate using principles of strong data design.
    • Built interactive Excel and SSRS reports based on business data.
    Technologies: KML, MySQL, PHP, JavaScript, .NET, C#, SQL Server Integration Services (SSIS), Microsoft SQL Server, COBOL, AS/400, ETL, Bash, Bash Script, Transact-SQL, HTML, CSS, Object-oriented Programming (OOP), SQL Stored Procedures, Stored Procedure, T-SQL, Databases
  • Sales Manager

    2006 - 2009
    Vector Marketing
    • Sold $60,000 in Cutco Cutlery in customers' homes personally.
    • Created $98,000 in new business by managing a seasonal branch office in Columbus, GA.
    • Conducted individual and group interviews, ran training classes, and managed a team of sales reps.
    Technologies: Sales, Management

Experience

  • Legomena
    https://github.com/victordavis/legomena

    A personal passion project developed and maintained a PyPi package complementing a computation linguistics paper published in Glottotheory (https://arxiv.org/pdf/1901.00521.pdf). The paper explores and refines ideas in information theory and NLP, particularly with regard to Heaps' Law.

  • Fast Character-level N-gram Language Model for Research Purposes
    https://github.com/VictorDavis/chlengmo

    I created this character-level N-gram language model package because I found the online tutorials for working with NLTK quite cumbersome, confusing, and slow. N-gram models are nowhere near the cutting edge of language modeling. However, they are still useful for establishing baselines, running simple information, like theoretic experiments and calculations, and overall useful for NLP research. This package is fast and truly plug-and-play.

  • Minimum Spanning Cones in 2, 3, 4 Dimensional Space
    https://github.com/VictorDavis/conebound

    I worked on this exciting math and optimization problem relevant to graphics, GPU computing, and geospatial analysis: What is the minimum aperture angle of a cone apex at the origin containing n random points in d-dimensional space? An even simpler version, do they all fall on one side of a (hyper)plane? This question represents a simple-sounding problem with very complex, inefficient dimension-specific solutions. Turns out to be a combinatoric, linear programming type problem, not necessarily geometric, and the established worst- and average-case solutions are not great.

Skills

  • Languages

    Python, R, SQL, JavaScript, PHP, Bash, Bash Script, Transact-SQL, HTML, CSS, Stored Procedure, T-SQL, Java
  • Paradigms

    Unit Testing, Test-driven Development (TDD), Object-oriented Programming (OOP), Data Science, Object-relational Mapping (ORM), ETL, REST, Management
  • Other

    Mathematics, Data Queries, Back-end, Data Analysis, Statistics, Artificial Intelligence (AI), APIs, Data Analyst, Analytics, Data Modeling, Predictive Modeling, Predictive Analytics, Text Analytics, Machine Learning, Natural Language Processing (NLP), Clustering, Data Analytics, Linear Regression, Logistic Regression, Statistical Analysis, Statistical Modeling, Model Validation, Monte Carlo Simulations, Markov Chain Monte Carlo (MCMC) Algorithms, Monte Carlo, AWS, Financial Modeling, Sales, 3D Math, Linear Optimization, Data Visualization, Fintech, API Integration, XAMPP Stack
  • Frameworks

    Flask, RStudio Shiny, JSON Web Tokens (JWT)
  • Tools

    GitHub, Git, Microsoft Excel
  • Platforms

    RStudio, Linux, Jupyter Notebook, Amazon Web Services (AWS), Docker, Amazon EC2 (Amazon Elastic Compute Cloud), AWS Lambda, LAMP
  • Storage

    MySQL, Microsoft SQL Server, Databases, Redshift, Amazon DynamoDB, SQL Stored Procedures, JSON
  • Libraries/APIs

    Scikit-learn, TensorFlow, Pandas, NumPy, API Development, REST APIs

Education

  • Bachelor of Science Degree in Mathematics
    2005 - 2007
    Southern Polytechnic State University - Marietta, Georgia, USA

Certifications

  • AWS Certified Cloud Practitioner
    OCTOBER 2021 - OCTOBER 2024
    AWS
  • AWS Certified Machine Learning – Specialty
    SEPTEMBER 2021 - SEPTEMBER 2024
    AWS
  • Data Science Specialization
    APRIL 2016 - PRESENT
    Johns Hopkins University

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