Lead Data Scientist

Job Description

Location: Kathmandu, Nepal (Remote)

Type: Part-Time or Full-Time

About the Role

We are seeking a Lead Data Scientist to join our Altus Minds team. The candidate will primarily work with our client, an innovative women's health technology startup. This is an exceptional opportunity to leverage data science to make a meaningful impact on women's health outcomes while working in a fast-paced, entrepreneurial environment as part of their data team. 

What We're Looking For

Essential Qualifications:

• Minimum 8 years of relevant data science experience with a proven track record of spearheading data initiatives within early-stage startups and demonstrated ability to work autonomously
• Advanced proficiency in Python and SQL with strong programming fundamentals
• Hands-on experience with modern data infrastructure including Google BigQuery, Firestore, Firebase, Google Analytics, and visualization platforms like Chartio or Tableau
• Expertise in specialized analytics including:

1. Time-series and behavioral data modeling
2. Anomaly detection and clustering algorithms
3. Outlier identification and scoring methodologies
4. Pattern recognition and foundational machine learning techniques

• Passion for transforming data insights into testable hypotheses that inform strategic product decisions
• Results-driven mindset with strong execution capabilities and ability to quantify business impact
• Strategic thinking to identify and prioritize insights that deliver maximum value to our user community
• Background working with healthcare data and comprehensive understanding of privacy regulations and security protocols

Preferred Qualifications:

• Data consulting or client-facing analytics experience
• Advanced expertise in Machine Learning and Deep Learning frameworks
• Previous experience in health and wellness technology companies
• Technical background in backend technologies (Node.js, GCP, etc.)

Key Responsibilities

Data Intelligence & Insights:

• Develop sophisticated individual-level analytics to uncover trends, behavioral patterns, and predictive insights including most frequently tracked health metrics and personalized recommendation effectiveness
• Transform complex personal health data into actionable, user-friendly insights that motivate positive behavior change
• Conduct comprehensive comparative analysis across individual users, cohort segments, and population demographics to identify strategic opportunities

Algorithm Development & Enhancement:

• Optimize and evolve proprietary algorithms powering our mobile application, including menstrual cycle predictions, symptom forecasting, inclusive predictions for diverse user populations, and proactive health condition screening
• Drive continuous improvement of predictive models based on user feedback and clinical validation

Strategic Data Partnerships:

• Synthesize population-level insights for brand partnerships and research collaborations
• Develop comprehensive health analytics reports that reinforce our reputation as a scientifically rigorous, data-driven organization

Infrastructure & Architecture:

• Assess and recommend optimal data platforms, pipeline architectures, and infrastructure solutions to ensure robust scalability, stringent security compliance, and seamless accessibility across teams