Data Scientist ( 3+ years Exp)

TIKET2RYDE/TRANZ. LLC

United States

13 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Experienced

Experience required

3 years minimum

Working hours

Regular working hours

Job source

arc.dev

Tech stack

A/B Testing Data Analysis Artificial Neural Networks Big Data Cluster Analysis Computer Programming R (Programming Language) Statistical Hypothesis Testing Python (Programming Language) Machine Learning SQL Databases Support Vector Machine

+5 more

Random Forest Deep Learning Model Validation Information Technology Data Pipelines

Job description

Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
Design, build, and validate robust data models and machine learning/ deep learning algorithms to improve customer experience, optimize revenue, refine targeting, and support smarter decision making across the organization.
Plan, monitor, and evaluate A/B tests and other experimentation activities for ML models, including test design, success metrics, and model performance assessment.
Collaborate closely with machine learning engineers, and other stakeholders to productionize models, build scalable data pipelines, and ensure reliable deployment and monitoring of ML solutions.
Implement processes, dashboards, and tools to monitor data quality, model performance, and business impact, and iterate on solutions based on findings.
Communicate insights, trade-offs, and recommendations clearly to both technical and non-technical audiences through reports, visualizations, and presentations.

Requirements

Minimum 3 years of hands-on experience in data analysis and machine learning, ideally in a product-driven or business-focused environment.
A Bachelor in Computer Science, Statistics, Mathematics, or another quantitative field.
Strong problem solving skills with an emphasis on product development.
Proficient in programming skills (R, Python, SQL, etc.) for data acquisition, processing and analysis from large data sets.
Knowledge of data science concepts (regression, classification, clustering, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
Knowledge of a variety of machine learning techniques (Random forest, SVM, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Excellent written and verbal communication skills for coordinating across teams.
A drive to learn and master new technologies and techniques.