Possible expired job

This job was posted 9 months ago and may be expired now. If that's the case, you can browse similar jobs here. Apologies for the inconvenience.

Lead Data Scientist

Lead Data Scientist

  • Product & Engineering

About the Company

Lift Ventures, a remote-first startup studio whose portfolio of businesses has reached over 250 million consumers to date, is seeking a seasoned and talented Lead Data Scientist for SuperSummary.com, our fast-growing EdTech business. SuperSummary is a subscription-based website offering a library of professionally written study guides and other educational resources on thousands of books for students, teachers, and readers of all types.

At SuperSummary, data drives our most important decisions including what in-demand literature titles to cover next in our Study Guide Library, what features to build next for our users, and what new markets to consider as we expand the scope of our business. We are looking for a Lead Data Scientist to oversee our most important data science and data analytics projects and work with other data-driven team members to take our advanced analytics operations to the next level.

About the Job
As Lead Data Scientist, you will plan, manage, and execute on projects that leverage large volumes of data across many sources. With the support of a small team, you will help accelerate our progress across projects spanning predictive analytics, data mining, and web data scraping/aggregation. You will leverage cutting-edge machine learning, AI, and natural language processing techniques to support important product and content decisions and accelerate the growth of our subscription business. Given the flat structure of our team, you will have the ability to make a significant impact from day one and make important decisions that influence millions of users.

This role is 100% remote. Our fully remote team is distributed across the globe with the majority of the team working in the United States, Brazil, and the Philippines.

Key Responsibilities
In this role, you will strike a balance between acting as a team lead/manager of a small team and working as a senior-level individual contributor on our most challenging data projects. You will also have the opportunity to work closely with senior leadership, including our VP of Operations and CEO. Your primary responsibilities within each functional area are:

Data Collection and Analysis:

  • Oversee the collection, organization, and aggregation of large data sets across dozens of internal and external data sources.
  • Build expert knowledge of all data sources in order to answer questions and support projects across the organization
  • Own the ETL process across the company: cleaning, structuring, enriching data; building cloud-based data lakes/warehouses leveraging modern best practices
  • Continuously monitor data quality and ensure data integrity and accuracy

Predictive Analytics and Machine Learning:

  • Apply state-of-the-art algorithms relying on knowledge of statistical modeling, machine learning, and optimization to develop new processes and improve the performance of our business
  • Build, evaluate and optimize models which incorporate machine learning and artificial intelligence
  • Enable migration to new cloud-based ML stack: data, model and deployment
  • Stay up-to-date with the latest trends, techniques, and software in data science and data analysis

Team Management and Collaboration:

  • Define the company’s data science roadmap, setting quarterly priorities that align with our overall vision and business objectives
  • Manage a team that includes a data scientist, scraping experts, and multiple data collection/research team members
  • Define all team project requirements and host weekly team syncs to establish task deadlines, monitor progress, and evaluate results
  • Identify and report on relevant team KPIs, and report progress across projects to senior leadership on both a monthly and quarterly basis
  • Collaborate with internal and external stakeholders across our Product, Content, and Operations teams to understand business goals and launch new data projects
  • Partner with Engineering team to transition development projects to production systems
  • Develop thorough documentation for all data science sources and projects

Business Intelligence and Reporting:

  • Use data visualization tools (Tableau, Metabase etc.) to manipulate and translate raw data into useful reports and dashboards
  • Surface key insights and trends across data sources that can help support business decisions

Requirements

Qualifications

  • 6-8+ years of experience in advanced data science and analytics roles, preferably in high-growth, dynamic environments (with 3+ years of in-depth predictive modeling/forecasting experience)
  • Extensive experience with cloud-based data collection, management, and automation (data scraping, ETL, data warehouses/lakes, etc.)
  • Hands-on experience with advanced methods in machine learning, data mining, statistics, optimization, classification, forecasting and/or NLP
  • Advanced experience with database languages (e.g. SQL) and statistical programming languages (e.g. Python, R, etc.)
  • Experience visualizing, synthesizing, and presenting complex data for stakeholders using tools like Metabase, Tableau, etc.
  • Excellent problem-solving skills and ability to identify opportunities to leverage AI, innovative software, and automation solutions
  • Strong past experience with data project management, team management, delegation, and cross-functional communication
  • Strong attention to detail and ability to manage/oversee multiple projects simultaneously
  • Bachelor’s degree in Computer Science, Data Science, Mathematics or similar quantitative field
  • Prior experience working in a lean, small company/startup environment is a plus, as well as prior exposure to businesses in similar or related fields (EdTech, consumer subscription/e-commerce , SaaS, books/media, etc.)

Perks and Benefits

  • Work with a distributed, global team that has been remote-first since 2018
  • Competitive salary, benefits, and vacation policy
  • Workspace improvement stipend
  • Professional development and learning stipend