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Data Science Intern

Skillify
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Internship Job Description — Kinship Labs

Position Title: Data Science Intern

Company: Kinship Labs

Location: Las Vegas, NV (In-Person)

Duration: 3 months

Hours: Full-time, Monday–Friday, 9:00 AM – 5:00 PM (40 hours/week)

Compensation: Paid Monthly Stipend

Level: Graduate (Master's preferred) or exceptional Bachelor's candidates


 

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Company Overview

Kinship Labs builds AI-powered relationship management software that helps organizations maintain personalized, human connections at scale. Our platform automates multi-channel communication (SMS, Email) while preserving authentic engagement through intelligent AI agents. We serve education, healthcare, and customer success teams managing hundreds to thousands of relationships.


 

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Position Description

The Data Science Intern will work directly with the engineering and product teams to build analytics infrastructure, define key metrics, and surface insights that drive business decisions. This is a hands-on role involving real production data, customer analytics, and direct impact on how we measure success.


 

Work Environment: Full-time office setting with a small, collaborative team. The intern will have a dedicated workstation, access to professional AI tooling (Claude, OpenAI, etc.), and direct mentorship from senior engineers.


 

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Primary Responsibilities

  1. Metrics Dashboard Development (60%)
    1. Design and build business intelligence dashboards for the Skillify and Kinship platforms
    2. Write SQL queries against PostgreSQL (Supabase) to extract engagement, pipeline, and communication metrics
    3. Create visualizations for key performance indicators (KPIs): response rates, pipeline progression, message volume, user engagement
    4. Collaborate with stakeholders to define meaningful metrics that drive business decisions
    5. Build automated reporting pipelines for recurring analytics needs
  2. Data Analysis & Insights (30%)
    1. Conduct cohort analysis to understand user behavior and retention patterns
    2. Analyze pipeline conversion rates and identify bottlenecks
    3. Design and support A/B testing frameworks for product experiments
    4. Build predictive models for churn risk, engagement scoring, or pipeline forecasting
    5. Present findings and recommendations to the team in weekly reviews
  3. Documentation & Knowledge Transfer (10%)
    1. Document data pipelines, queries, and dashboard architecture
    2. Create runbooks for ongoing metrics maintenance
    3. Build a data dictionary for key tables and business definitions


 

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Program Learning Objectives

By the end of this internship, the student will be able to:

  1. Design data pipelines and dashboards — Build end-to-end analytics from raw database queries to stakeholder-ready visualizations
  2. Write production SQL — Query relational databases (PostgreSQL) for complex business analytics including joins, aggregations, window functions, and CTEs
  3. Conduct rigorous analysis — Apply statistical methods to answer business questions and validate hypotheses
  4. Define and track KPIs — Translate business goals into measurable metrics and build systems to track them
  5. Use modern development workflows — Work with Git/GitHub, code review, and collaborative development practices
  6. Communicate technical findings — Present data insights and recommendations to non-technical stakeholders


 

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Required Qualifications

  • Currently enrolled in or recently completed a Master's program in Data Science, Statistics, Information Science, or related field (exceptional Bachelor's candidates considered)
  • Coursework in statistics, machine learning, or quantitative analysis
  • Proficiency in SQL (intermediate level)
  • Familiarity with Python for data analysis (pandas, numpy, matplotlib/seaborn)
  • Strong written and verbal communication skills


 

Preferred Qualifications

  • Experience with dashboard/visualization tools (Metabase, Tableau, Looker, Superset, or similar)
  • Familiarity with Git and GitHub
  • Experience with PostgreSQL or similar relational databases
  • Exposure to dbt, Airflow, or other data pipeline tools
  • Kaggle competitions, research projects, or analytics portfolio work


 

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Technical Environment

  • Database: PostgreSQL via Supabase (read access)
  • Languages: SQL, Python, JavaScript
  • Backend Context: Node.js, Express, Prisma ORM
  • Version Control: Git/GitHub
  • Communication: Slack


 

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The intern will receive:

  • Daily check-ins with progress review
  • Weekly 1:1 mentorship sessions
  • Direct access to senior engineers for technical guidance
  • Code review and feedback on all work


 

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Path to Full-Time Employment

This internship is designed with a potential transition to a full-time role in mind. At the conclusion of the 3-month program, candidates who demonstrate strong performance may be offered a full-time position as a Data Scientist or Analytics Engineer at Kinship Labs.


 

Criteria for full-time consideration:

  • Consistent delivery of high-quality work throughout the internship
  • Strong collaboration and communication with the team
  • Demonstrated ability to work independently and solve problems proactively
  • Alignment between the candidate's career goals and Kinship Labs' business needs


 

Final hiring decisions will depend on mutual fit, business needs, and available funding at the time of evaluation. We are a growing startup and prioritize retaining talent that contributes meaningfully to our mission.