My Resume

Experience

Senior Sales Engineer

2023 - Present

Design and deliver technical demos across enterprise search and ecommerce use cases, including semantic and vector search plus GenAI/RAG experiences.
Partner with account executives through full pre-sales cycles: discovery, solutioning, technical deep dives, and security/integration discussions.
Advise customers on data ingestion and integration patterns (APIs, cloud storage, and databases) and apply AI-driven enrichment during indexing to improve retrieval quality.
Build rapid prototypes and proof-of-concepts that translate real-world requirements into working solutions under tight timelines.
Work hands-on with LLM and modern AI stacks including embeddings, retrieval strategies, prompt patterns, and model endpoints, balancing quality, latency, and cost.
Collaborate with Product and Engineering by feeding back field learnings, feature gaps, and competitive insights to improve roadmap and demoability.

Pre-Sales Solutions Architect

2022 - 2023

Utilized SQL/Presto/Hive, ML solutions, Kafka, Snowflake, JavaScript, Python, APIs/Integrations, and workflow automation to deliver technical demonstrations.
Lead presentations, product demos and provided technical consultations to prospects, helping to understand their needs and the capabilities and benefits of the software.
Answered RFPs and conducted product development discussions, providing feedback and insights on customer needs and trends.

Machine Learning Solution Architect

2020 - 2022

Established the architecture, technical specifications and oversaw the implementation of complex, custom, cloud-based (GCP) machine learning solutions.
Counseled customers as the lead technical product and machine learning expert to meet and exceed client business needs.
Set priorities based on project requirements and serve as a technical escalation point to developer, ML, QA, DevOps, and support teams.

Product Manager

2019 - 2020

Owned and oversaw the execution of a platform to automate, scale and provide monitoring to support and aid implementation of Arcadia’s software and the integration & ETL of 1000s of data sources.
Managed the backlog and work queue & sprints for the platform back-end team and web team.

Technical Implementation Team Manager

2017- 2019

Managed twelve employees across two technical product implementation teams.
Developed a full-stack set of applications to monitor real time operational metrics across the organization using D3, Python, SQL, Node.js and multiple APIs.
Chosen to be on an executive SWAT team to fully revamp and redevelop the implementation process within AWS, leveraging Spark, machine learning algorithms and a redesigned lean process workflow.

Solutions Architect

2015 - 2017

Led client engagements to capture requirements, articulate Arcadia's technology capabilities, and devise customized architectural plans, ensuring alignment with clients' strategic objectives and successful product implementation.
Established technical requirements and oversaw their completion across multiple teams.
Created a predictive model to predict the likelihood of a patient being a no-show to a scheduled doctors appointment based on dozens of data points.

Senior Consultant

2013 - 2015

Served as the tech lead onsite for a major insurance client at the onset of the HealthCare.gov integration and enrollment reconciliation.

Consultant

2012 - 2013

Worked to integrate and analyze data from multiple clients connecting to an array of EHR (Electronic Health Record System) and Health Plan data sources.
Lead the UX/UI effort for the creation of a large custom enterprise application.

Education

Northeastern University

B.S. Industrial Engineering

General Assembly

Data Science

Boston, MA

Visual Design

Boston, MA

Technical Skills

Coding

Python

JavaScript

SQL

D3.js

Node.js

jQuery

HTML/CSS

Cloud

AWS

GCP

Azure

AI / Search

LLMs

RAG

Embeddings

Vector Search

Prompt Design

Database

SQL Server

BigQuery

Presto

Snowflake

Postgres

Redis

Misc

Message Queue/Streaming

Docker

Kubernetes

pySpark

Pandas

Jupyter

Git

Scikit-learn

Jira

APIs/Integrations

Jenkins

Patent

Automated Splitting of Document Packages and Identification of Relevant Documents

Patent Published — US11789990B1

Co-author — 17/733,581

View published patent

Employee of Year

2016 Arcadia Analytics Award

Enterprise Clients

Experienced presenting to and working with large companies

Six Sigma

Six Sigma Yellow Belt

My Areas of Focus

SaaS Software

Over 10 years of experience with selling, implementation and supporting SaaS software across multiple industries. I am specifically experienced with cloud software which focuses on data integration, transformation and analytics. Treasure Data's CDP and Arcadia's Analytics platforms are two prominent examples.

Product Management

Experience with Agile methodologies (Scrum, Kanban), grooming and planning backlogs. Experienced as a Jira Admin, creating, managing and supporting project workflows. My technical experience is a large asset in communicating with and gaining the trust of engineers. I have experience serving as product owner for platform, web, as well as internal automation and telemetry products.

Machine Learning

Have developed my own predictive models, as well as created an architectural plan to support larger production machine learning stacks. At Iron Mountain, my team and I received a patent for a document splitting and identification model that we developed for our large lender clients. At Arcadia, while using clinical, claims, and demographic data I built a predictive model to predict how likely a patient would be a "No Show" to their doctor appointment.

Database Expertise

Highly experienced with creating, managing and architecting databases. Very strong SQL skills and have created very complicated queries, stored procedures as well as integrations via APIs to external systems. Both SQL and NoSQL databases. Have conducted data model designs, database development standards, implementation and management of data warehouses and data analytics systems.

Cloud Tech

Have worked across AWS, Azure and GCP. And have years of experience using and architecting cloud services and software. Have used cloud data products like Snowflake, Databricks, Splunk and Elastic. Have experience using and coming up with architecture using streaming services like SNS, Pub/Sub, Kafka. Also have experience with both serverless services like Lambda, as well as VMs and containers in the cloud.

Business Minded

Have worked across several industries (Healthcare, Insurance, Consumer, Pharma, etc.). Presented to C-Suites. Have accrued years of client-facing experience, starting with onsite weekly consulting earlier in my career. I enjoy learning about businesses and industry trends, and even outside of work I stay up to date on business, tech news and review quarterly earnings reports of public companies I follow.

Process Focused

As an Industrial Engineer by training, I have a mind for process improvement, efficiency and using data to make business decisions. I am Six Sigma certified and a strong believer in measuring outcomes to learn and make better informed business decisions from.

Full Stack

Have written full stack applications using Python, Node, JavaScript and SQL as well as integrating data from numerous external systems via APIs, message queues, ETLs and webhooks. Am familiar with a lot of common JavaScript libraries like jQuery, Bootstrap, Angular, D3.

Data Visualization

Experienced with creating custom, and sometimes interactive, javascript visualizations using D3. Additionally have created dashboards and models with Sisense, QuickSight, Tableau, PowerBI, Qlik. You can view some examples here. I am also proficient with Adobe Illustrator, Photoshop and Xd.

My Portfolio

Data Quality Scorecard Search Success Metrics ETL Telemetry Workflow Capacity Planner Infographics Finance ML Model

Download free bootstrap 4 admin dashboard, free boootstrap 4 templates

Database Job Monitoring

A real time database job monitoring dashboard I created, using D3 in the front end, Node.js and SQL Server in the back-end.

ETL Timeline Telemetry

A real time database job monitoring dashboard I created, using D3 in the front end, Node.js, Python and SQL Server in the back-end.

Data Quality Scorecard

Interactive set of D3 dashboards that in real time read a set of flat files from S3, and turned them into a set of charts making the output much easier to understand. I built the full webapp using a Node Express server, Python for data integration and transformation and D3 and other JavaScript libraries for the front end.

Data Quality Scorecard

Search Success Metrics Dashboard

Built an interactive dashboard to evaluate and clearly communicate search relevance lift across multiple retrieval strategies, combining key metrics (nDCG, MRR, Success@K) with an LLM-as-judge to score result quality at scale—so stakeholders can quickly see which approach improves relevance and why.

Search Success Metrics Dashboard

Data Quality Scorecard

Interactive set of D3 dashboards that in real time read a set of flat files from S3, and turned them into a set of charts making the output much easier to understand. Built using a Node Express server, Python for data integration and transformation and D3 and other JavaScript libraries for the front end.

Workflow Capacity Planner

Interactive work scheduling application I developed using a myriad of data sources including a python JIRA API integration, as well as data collected from database, and logs & files from AWS.

Near Real Time Stock Dashboard

Using a GCP cloud function, running a python script to obtain latest stock data from yahoo finance API for a set of stocks on my stock watchlist. The output is displayed in realtime, in a custom chart made using D3.

Economic Dashboard

Built an interactive macroeconomic dashboard that pulls live Federal Reserve (FRED) data to track key indicators over time and analyze how they relate—letting users choose series, time ranges, recession shading, and rolling correlation windows to quickly explore trends and co-movement without digging through raw datasets.

Infographic Using Public Data

Infographic for a poster used at a conference, made in D3 and Adobe Illustrator, using publicly available data. Read more here: https://arcadia.io/resources/burgers-and-fries

Appointment No Show Model

The model was made to predict “No Shows” from clinical & claims data. “No Shows” are appointments which a patient makes, but doesn’t show up for, cancel or reschedule prior

Benefits of Predicting No Shows

Target outreach, additional appointment reminders or other services like at home visits, transportation or assistance from social workers Target the cross section of likely “No-Shows” & High-Risk patients

Past Behavior

For each appointment, the status of the previous appointment (Kept, No-show, etc.) was obtained along with number of previous appointments, and the patients trailing appointment behavior (ex. 25% cancelled, 25% no show, 50% kept)

Getting the Data

The first step was to obtain data for each appointment for a given time and relative information like time of day, when the appointment was made, etc.

Demographics

The next step was to obtain patient demographics such as age, gender as well as patient chronic conditions and past diagnoses

Distance to Appointment

Created Python script which used the Google Maps API to retrieve coordinated for each location, based on the practice name Found a lookup table to map patients ZIP codes to coordinates and used Haversine formula to find distance between the two sets of coordinates

Income

Used publicly available income information to approximate income by patient zip code

Provider Specialty

Grouped several categories and select the top reasons and specialties as features

Tuning The Model

Used Python and SQL to transform nominal features (ethnicity, gender, etc.) into binary features (ex: female: 1/0; male: 1/0). The features were normalized to have the same initial weight.

Selecting The Model

Using different hyperparameter as well as models to choose best model and parameters. Evaluated: Decision Tree vs K Nearest Neighbor vs Random Forrest vs Ridge Classifier vs Logistic Regression

About Me

Solving Complex Problems With Better Processes, Data, and AI

Personal Info

My Expertise

Technical Pre-Sales

Data Science & AI

Product Management

Technical Team Management

My Resume

Experience

Senior Sales Engineer

Pre-Sales Solutions Architect

Machine Learning Solution Architect

Product Manager

Technical Implementation Team Manager

Solutions Architect

Senior Consultant

Consultant

Education

Northeastern University

General Assembly

Technical Skills

Coding

Python

JavaScript

SQL

D3.js

Node.js

jQuery

HTML/CSS

Cloud

AWS

GCP

Azure

AI / Search

LLMs

RAG

Embeddings

Vector Search

Prompt Design

Database

SQL Server

BigQuery

Presto

Snowflake

Postgres

Redis

Misc

Message Queue/Streaming

Docker

Kubernetes

pySpark

Pandas

Jupyter

Git

Scikit-learn

Jira

APIs/Integrations

Jenkins

Patent

Automated Splitting of Document Packages and Identification of Relevant Documents

Employee of Year

Enterprise Clients

Six Sigma

My Areas of Focus

SaaS Software

Product Management

Machine Learning

Database Expertise

Cloud Tech

Business Minded

Process Focused

Full Stack

Data Visualization

My Portfolio

Database Job Monitoring

ETL Timeline Telemetry

Data Quality Scorecard

Data Quality Scorecard

Search Success Metrics Dashboard

Phone :
(781) 572-7467

Location :
Boston, Massachusetts

Email :
smnioffe@gmail.com