Data Scientist $4000-6000 Offline

About The Client

YouTube audience development and management suite that helps brands and agencies grow

their views and subscribers. It is an end-to-end solution that assists YouTube Marketers at every step of their workflow, including uploading their videos at the best time of day, connecting brands with their top influencers, YouTube SEO, monitoring viewer and engagement analytics across Twitter and Facebook, bulk description editing, comment moderation, and Facebook fan page syndication.

About the Project

The client develops online education website that offers video tutorials and analytics on YouTube channel growth. The website also has a Google Chrome extension, which allows users to analyze YouTube analytics data.

The mission is to advance the creator's journey with actionable data-driven insights. We pursue this through our values of being creator obsessed, lean and fast, and being scientific.

We have already helped millions of creators take their channels to the next level. Simply put, we change lives.

What you will be doing

• Help build the machine learning-powered algorithm products that make vidIQ a leader in the video analytics space

• Design, prototype, help engineers to implement, and A/B test innovative algorithms that work at scale, drawing on recommender systems, natural language processing, computer vision, and other relevant domains

• Be an advocate for and help to identify new machine learning and AI product opportunities for the business

• Work closely with cross-functional teammates, including product managers, engineers, designers, and product analysts, to deliver the highest impact to our users

Job responsibilities

• Knowledgeable with 3+ years of relevant industry experience and advanced degree in machine learning, computer science, statistics, biostatistics, mathematics, or related quantitative field

• Proven track record of shipping machine learning-powered algorithm products at B2C-like scale as well as working with cross-functional teams in an agile-like environment

• Your grasp of machine learning fundamentals and ability to design intuitive, working ML solutions in response to complex business problems

• You have a strength in the “design and prototype” part of the ML development pipeline, beginning with pulling datasets from SQL and ending with serializing ML models and assisting engineers to product-ionize model retraining and model serving systems

• When it comes to communicating, you have no problem with ML/algorithm designs clearly to cross-functional team members, especially engineers and product managers

• You are well versed in SQL data warehouses such as Redshift and Snowflake, have worked on current ML tools such as TensorFlow, PyTorch, and Python, and feel comfortable with recommender systems or natural language processing

• To take it one step further, you are effective at translating and blending traditionally distinct ML concepts such as recommender systems, NLP, regression, andиclassification into a common framework such as TensorFlow

Selection Proces:

*- management interview

• technical interview

• client management interview*