Clio Logo

Base City: 

Remote-Canada - Remote

Salary: 

$134k to $182k

Rating: 

Self-taught: 

Position Type: 

Full-time

Position Keywords: 

Required: 

Bachelor - Computer Science

Experience: 

5 Years Data Science

Other Experience: 

  • 5+ years applied experience in data science.
  • Experience in analytics working with product and user behavior data, e.g., retention or churn analysis.
  • The ability to translate business requirements into data science solutions.
  • Proficiency in database modeling, SQL, and data warehousing principles.
  • Proficiency in developing analysis in Python and experience with relevant ML libraries and frameworks (e.g., pandas, PyTorch, scikit-learn)
  • Proficiency with building ML/AI pipelines and relevant tools (e.g., Kedro, MLFLow)
  • Strong team player mindset, while able to work under your own initiative and prioritize time and tasks effectively.
  • Excellent written and verbal communication skills.

Serious bonus points if you have:

  • A deep understanding of SaaS business metrics and growth drivers.
  • Experience with FinTech concepts.
  • Experience with large data sets and user behavior data.
  • Experience with NLP and LLMs.
  • A graduate degree in a relevant quantitative discipline (computer science, statistics, mathematics, physics, engineering)

About the Job: 

Clio is more than just a tech company–we are a global leader that is transforming the legal experience for all by bettering the lives of legal professionals while increasing access to justice.

Summary:

We are currently looking for a new Senior Data Scientist, to join our Data Insights team and work closely with Clio’s products and business teams.

You thrive on both analytical challenges and working closely with product development and customer-facing professionals. You will collaborate with everyone from product managers to business leaders and developers, and will guide rapid iterations of hypothesis, prioritization, experimentation / analysis and strategy setting – extract valuable insights, enhance our decision-making processes and contribute to the development of innovative financial products.

The Team:

You will be working alongside a cross-functional team of data scientists, embedded within Clio’s products and business teams, developing AI and ML solutions to understand Clio’s customers, to bring them cutting-edge AI and GenAI products, and to recommend proactive and efficient ways to serve them better. You will play an integral role, enabling business leaders across Clio make rigorous data-driven decisions. You will help our business grow, help our customers succeed, and continuously improve the way we operate.

What they want you to do: 

We aren’t looking for just any traditional Data Scientist to join this team. We’re looking for someone who takes data seriously, thrives in a rapid-growth, high-velocity environment, and lives and breathes our values. We’re looking for an innovator and a thought leader! We’re looking for someone who is:

  • Passionate about driving growth empirically;
  • Always looking to innovate with data and explore open-ended questions;
  • Strategically minded and never shies away from a challenge;
  • Self-motivated and able to work autonomously and collaboratively;
  • Agile and responsive, and comfortable with constant change.

You will help lay the foundation for this work by ensuring good data quality, data governance, and analytical practices. And you will also be part of our larger Data & AI team for learning, career development, and company-wide data initiatives.

Here’s what you’ll need to do:

  • Collaborate with the Clio products teams to identify opportunities, develop hypotheses, and provide input that drive growth.
  • Identify new questions about our business, product, and customers that lead to impactful insights.
  • Build predictive and prescriptive AI and ML solutions and deploy them in production.
  • Apply rigorous statistical analysis and data mining techniques to evaluate impact of different product features and other business initiatives.
  • Innovate and experiment with new applications of statistical analysis, machine learning, GenAI, LLMs, etc. to unlock new product opportunities.
  • Build a scientific culture in product and business teams by enabling discussions with data, disseminating best practices, and leading by example.
  • Effectively communicate complex technical concepts and findings to both technical and non-technical audiences.

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