Title: Machine Learning Engineer

Location: Hybrid only 3 days/ monthly onsite to Basking Ridge, NJ (Every Tuesday except first week of the month )

Duration: Long Term Contract

Client: Verizon

on C2C

Duration: Long Term contract.

Responsibilities

Develop, implement and distribute large-scale, scalable web apps for data science and machine learning solutions

Maintain and improve data pipeline using machine learning infrastructure and existing machine learning models

Data manipulation and statistical modeling

Time series forecasting model using ML and deep learning techniques

Develop the core functionality of Plotly's enterprise products, with a particular focus on Dash application management capabilities (similar to Heroku)

Improve reliability, testing, automation, observability, and performance throughout our stack

Written and verbal technical communication skills with an ability to present complex technical information in a clear and concise manner to a variety of audiences

Experience Required

5+ years of experience as a data scientist, applied scientist, data analyst, machine learning engineer or a related role

Bachelor's degree in Math, Physics, Statistics, Economics, Computer Science, or similar domain

Proficiency in Python (including packages like numpy, pandas, sklearn, pytorch, tensorflow, matplotlib), SQL and Excel. Experience with Dash Plotly is a plus

Experience working with demand forecasting, supply chain optimization, driver analysis, time series analysis, statistical models, regression models and deep learning models

Experience working on various steps of developing a data science solution, like problem scoping, data gathering, EDA, modelling, insights, visualizations, monitoring and maintenance

Ability to create efficient solutions to complex problems. Strong skills and solid foundation in data-structures, ML algorithms and pipeline development.

Problem-solving: Ability to break the problem into small parts and applying relevant techniques to drive required outcomes

Expertise in exploratory data analysis, visualization, ETL, hypothesis testing, experimentation, automation, etc.