Data Scientist (Ph.D.)

Boo Indonesia
Remote
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AI Summary

We are seeking a highly quantitative Data Scientist with a Ph.D. in Mathematics, Statistics, or a related quantitative field to develop advanced algorithms and analytical models that power product innovation and data-driven marketing strategies.

Key Highlights
Develop, test, and optimize machine learning models, predictive algorithms, and statistical frameworks for product and marketing applications.
Conduct advanced data analysis using techniques such as Bayesian modeling, time series forecasting, causal inference, reinforcement learning, anomaly detection, or optimization algorithms.
Work with product teams to inform feature development, personalization strategies, experimentation design, and product roadmaps.
Technical Skills Required
Python Pandas NumPy SciPy scikit-learn PyTorch TensorFlow SQL
Benefits & Perks
Full-time employment
Remote work
Opportunity to work on high-impact algorithms that directly shape product and marketing strategy
Collaborative environment with multidisciplinary teams

Job Description


Job Description: Data Scientist (Ph.D.)

Position Title: Data Scientist (Ph.D.)

Department: Data Science / Product / Marketing

Reports To: Director of Data Science / Head of Analytics

Location: Remote

Employment Type: Full-Time


Position Summary

We are seeking a highly quantitative Data Scientist with a Ph.D. in Mathematics, Statistics, or a related quantitative field to develop advanced algorithms and analytical models that power product innovation and data-driven marketing strategies. This role sits at the intersection of data science, product development, and marketing, working closely with cross-functional teams to transform complex data into actionable intelligence and scalable solutions.


The ideal candidate is a strong researcher with a practical engineering mindset—comfortable developing novel models, testing hypotheses, and deploying solutions that drive measurable business impact.


Key Responsibilities

Algorithm & Model Development

  • Develop, test, and optimize machine learning models, predictive algorithms, and statistical frameworks for product and marketing applications.
  • Conduct advanced data analysis using techniques such as Bayesian modeling, time series forecasting, causal inference, reinforcement learning, anomaly detection, or optimization algorithms.
  • Build scalable solutions and partner with engineering teams to deploy models into production.


Cross-Functional Collaboration

  • Work with product teams to inform feature development, personalization strategies, experimentation design, and product roadmaps.
  • Collaborate with marketing to build customer segmentation models, attribution models, LTV forecasting, targeting strategies, and campaign optimization tools.
  • Translate scientific findings into clear business recommendations and partner with stakeholders to ensure adoption.


Data Exploration & Insights

  • Lead complex research initiatives—hypothesis formulation, experiment design, statistical validation, and result interpretation.
  • Analyze large datasets to uncover patterns, generate insights, and identify opportunities for product or marketing optimization.
  • Develop dashboards, metrics, and automated analytical systems to monitor model performance and business outcomes.


Experimentation

  • Design and evaluate A/B tests, multi-arm bandit experiments, and other controlled experiments to measure product and marketing impact.
  • Apply rigorous statistical methodologies to assess causal relationships and ensure scientific validity.


Documentation & Communication

  • Document model assumptions, methodologies, and results in a way that is clear, reproducible, and auditable.
  • Present findings and recommendations to leadership and cross-functional teams in a compelling and accessible manner.


Qualifications

Required

  • Ph.D. in Mathematics, Statistics, Applied Mathematics, Computer Science, or a related highly quantitative field.
  • Strong foundation in mathematical modeling, probability, statistical inference, and advanced analytics.
  • Proficiency in Python (Pandas, NumPy, SciPy, scikit-learn, PyTorch/TensorFlow preferred).
  • Experience building and deploying machine learning models end-to-end.
  • Experience working with large, complex datasets using SQL or similar tools.
  • Ability to communicate complex technical concepts to non-technical stakeholders.
  • Proven ability to work in cross-functional environments and manage multiple research streams.


Preferred

  • Experience in product analytics, digital marketing analytics, or algorithm development for consumer-facing applications.
  • Experience with cloud environments (AWS, GCP, or Azure).
  • Experience developing models for personalization, recommendation systems, LTV prediction, NLP, or optimization.
  • Experience with experiment design (A/B testing) and causal inference.
  • Experience with data visualization tools (e.g., Tableau, Looker) or programmatic visualization (matplotlib, seaborn, Plotly).


Key Competencies

  • Strong mathematical and statistical intuition
  • Research-driven, experimental mindset
  • Ability to translate complex quantitative work into business value
  • Curiosity, creativity, and scientific rigor
  • Strong communication and storytelling skills
  • Ability to work independently and as part of a cross-functional team


Why Join Us

  • Work on high-impact algorithms that directly shape product and marketing strategy
  • Collaborate with multidisciplinary teams and influence core business decisions
  • Opportunity to bring cutting-edge research into real-world applications
  • Supportive environment for ongoing learning, experimentation, and innovation


Location: Full Remote


******For Interested applicants: Send your updated resume, sample works/ portfolio and we would be asking you to take a personality test at this site https://boo.world/16-personality-test

Kindly send us the five letter results. (e.g. ENTJ-T) to queenie@boo.world together with links to your resume and sample works. Subject: Position you are applying for (e.g Data Scientist )


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