- Perform data discovery of stakeholders' needs, help design solutions, and collaborate with engineering on how their infrastructure should affect data transformation design.
- Design and enhance data models, schemas, quality testing, and database designs to support efficient data streaming in production.
- Partner where applicable to develop data documentation, including data dictionaries, data lineage, and integration processes.
- Collaborate with Engineering and Product teams to ideate on permutations data structures that cater to multiple enterprise-scale products and applications.
- Produce insights (e.g. performance drivers, retention analysis, behavioral personas) to accelerate adoption; this requires acquiring and cleaning data from multiple sources, structuring and building data models, analyzing to generate insights, and distributing them.
- Evaluate the performance of the LLM in different experimental conditions, such as variations in training data, fine-tuning techniques, or model architectures.
- Produce and build tracking of various product success metrics related to conversational quality, coherence, relevance, and user satisfaction.
- Minimum of 4+ years of work experience in a Product Data Science role.
- Full stack Data Science experience: Demonstrated success in bridging the gap between high-level project requirements and complex application data
- Data engineering: familiarity with engineering best practices and skills to build and deploy model pipelines to production.
- Data analysis and exploration: Exploratory data analysis skills are a critical tool for every full stack Data Scientist, and the results help answer important business questions.
- Applied Statistics - Statistical modeling and support of production systems. Understanding of statistical concepts and practical experience applying them (A|B testing, causal inference ).
- Proficiency in SQL and Python-based (pandas or pyspark) tooling for data transformation.
- Communication - You have a wealth of experience helping product teams make great decisions with data.
- Strong Data Visualization skills: Streamlit, Tableau, (Looker, PowerBI)
- Data modeling experience using dbt and other advanced data pipeline tooling
- Experience building data products
- Familiarity with machine learning (model training/evaluation, ML applications)
- Experience building effective data visualizations with tools like Streamlit or Tableau
Compensation & Benefits
The base salary/hourly wage that we reasonably expect to pay for this role is: $123,000-$185,000
The actual base salary/hourly wage for this role will be determined by a variety of factors, including but not limited to: the candidate’s skills, education, experience, etc.
Please note that base pay is one important aspect of a compelling Total Rewards package. The base pay range indicated here does not include any additional benefits or bonuses/commissions that you may be eligible for based on your role and/or employment type.
Regular full-time employees are eligible for benefits - see here.