Eliq

Engineering Manager - Insights

Head of Data

Genus AI

Leading and expanding a small team of data scientists with a focus on core platform capabilities.
Spearheading ML efforts for those capabilities - creative scoring, data enrichment, modeling business KPIs for paid social campaigns.

Took over a team of Data Scientist to streamline the delivery of business value to our customers.
Mentored and lead a small team of data scientists. Expended a team with data scientists with complementary skillset. Go-to person for all data science-related topics in the company.
Successfully delivered on big and small projects during a challenging lockdown period that required an unconventional approach to mapping business problems to ML problems. 
Personally and together with the team contributed back to the platform codebase to improve the efficiency correctness of the results. 
Build several POC product iterations before those were incorporated into the product.

Tools: Python, AWS, SageMaker, LightGBM, Arcanist

Lead Data Scientist - Machine Learning

Developed DL models for marketing creatives used in paid social campaigns. From different data vendors evaluation to data collection and training dataset preparation. From model building to model evaluation and selection for production.
Developed customer data enrichment pipeline that simplified and automated data enrichment process reducing cost and duration twentyfold.

Tools: Python, AWS, SageMaker, GCP, Arcanist

Senior ML Engineer

Sentiance

Steering team containing data and machine learning engineers as well as data scientists towards a common goal. Planning work increments and implementing part of the functionality.
Delivering ML functionality for highly specialized use-cases.

Senior Data Scientist

User behavior predictions - from enriched GPS data predicting next events for the user. Models spanning simple historical frequencies based model to complex RNN. Model evaluation for a highly complex problem, setting up monitoring and debugging environment for the deployed model.

Tools: Python, Docker, Kafka, Flask, Dash

Data Scientist

Exacaster

Leading a team of two data scientists for recommendation engine implementation for e-commerce clients.
Developed and released the first version of the customer 360 profile based on Spark.
Improved customer churn solutions and implementing relevant software engineering practices in data scientists workflow.

Tools: Python, Spark, Airflow, Git

Vinted / Kleiderkreisel

POC of content recommendation implemented as a Spark batch job.
Contribution to DWH source code for metric calculation.
Working closely with the PO while defining key results and setting up a tracking dashboard in the big data environment.

Tools: Spark (Scala), Spark Notebook,  SQL, python, d3 for visualization.

Data Scientist - Analytics

Danske Bank

SME rating process automation. Extracting data for process evaluation and proposing ML-based techniques that would simplify the process. Participating in discussions with rating officers about proposed process improvements and their impact on credit risk.

Tools: T-SQL, R (Tidyverse), Statistica.

SEB Lietuvoje

Market risk control function - keeping track of trading and market risks. Assurance of market data input for correct portfolio valuation.

Risk Officer

Working in the depository unit. Was responsible for assurance of NAV calculation and investment restrictions for pension, investment and RE funds.

Fund Administrator

Aarhus School of Business and Social Sciences

Supervision of "Fixed Income Securities" Study Cafe sessions.

Teaching Assistant

KPMG

Auditor's assistant

https://vaidasarmonas.medium.com/
https://va1da2-running-analytics-streamlit-app-fd3v8l.streamlitapp.com/

Experienced data science lead and full-stack data scientist with experience in IT, marketing, telecommunications, and financial services industries. Agile data science enthusiast and practitioner.

Contact: vaidas.armonas@gmail.com

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