Machine Learning Intern

Sunnyvale, California, United States

CommerceIQ

View company page

Company Overview

At CommerceIQ, we help consumer brands accelerate their retail ecommerce market share growth and profitability through machine learning algorithms. We are building the world’s most complete and sophisticated Retail Ecommerce Management Platform, which connects and intelligently automates the management of retail ecommerce channels like Amazon, Walmart, and Instacart, across the entire ecommerce operational chain of retail media management, sales operations, supply chain, and digital self analytics.

We are in hyper growth mode, having recently raised our Series D funding at unicorn valuation (>$1B) and ended our third year of triple-digit revenue growth. Continued acceleration of our growth is fueled by landing new customers, expanding our platform through new products, managing new retail ecommerce platforms, and delivering exceptional customer service to unlock high net retention rates.

As a Machine Learning Intern at CommerceIQ, you will have the opportunity to work closely with our product management team and gain hands-on experience in shaping the future of our products. This internship is ideal for candidates who are passionate about technology, data platforms, and enterprise SaaS products, and are looking to transition into product management roles. We are seeking talented individuals with a strong academic background from tier 1 schools, along with prior work experience as Software Engineers building data platforms or Data Scientists in enterprise SaaS product companies.

Responsibilities:

  1. Collaborate with product managers to define product roadmaps, features, and specifications based on market research, customer feedback, and business objectives.
  2. Assist in the prioritization of product features and enhancements, considering factors such as customer value, technical feasibility, and business impact.
  3. Conduct competitive analysis and market research to identify trends, opportunities, and threats in the industry, and make recommendations for product strategy.
  4. Work closely with cross-functional teams including engineering, design, marketing, and sales to drive the execution of product initiatives and ensure successful product launches.
  5. Assist in the development of product documentation, including user stories, wireframes, and product requirements documents, to communicate product vision and requirements to stakeholders.
  6. Analyze product performance metrics and user feedback to measure the success of product initiatives and identify areas for improvement.
  7. Support product managers in day-to-day activities such as coordinating meetings, tracking action items, and communicating updates to stakeholders.

Qualifications:

  • Currently pursuing or recently graduated from a tier 1 school,with a degree in Computer Science, Engineering, Business, or related field.
  • Minimum of 2 years of prior work experience as a Software Engineer building data platforms or Data Scientist in enterprise SaaS product companies.
  • Strong analytical and problem-solving skills, with the ability to understand complex technical concepts and translate them into product requirements.
  • Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams and communicate complex ideas clearly and concisely.
  • Proven ability to manage multiple projects simultaneously and prioritize tasks in a fast-paced environment.
  • Passion for technology, data platforms, and enterprise SaaS products, with a desire to learn and grow in the field of product management.

 

Apply now Apply later
  • Share this job via
  • or

Tags: Computer Science E-commerce Engineering Machine Learning Market research Research

Perks/benefits: Career development Startup environment Team events

Region: North America
Country: United States
Job stats:  76  39  0

More jobs like this

Explore more AI, ML, Data Science career opportunities

Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.