Data Scientist

Rose International; San Diego (CA); On-site; USD 110,000 - 140,000; Full time

Job summary

Rose International is seeking a Data Scientist located near San Diego, CA for an on-site role. The candidate will apply advanced SQL, Python-based analytics, and causal inference techniques to drive data-driven decisions.

Responsibilities include designing experiments, building scalable analytics solutions, and communicating insights to stakeholders. A Bachelor's is required; a Master's is preferred, with strong visualization skills using Qlik, QuickSight, Tableau, and Plotly Dash.

Qualifications

• Bachelor's degree in Statistics, Mathematics, Computer Science, or related field.
• 3-5+ years of experience with advanced SQL and data visualization tools.
• Experience with Python and statistical modelling libraries.
• Experience with causal inference techniques (PSM, diff-in-diff, synthetic control).
• Experience with Generative AI and leveraging multi-modal data insights.
• Ability to design experiments beyond traditional A/B tests.
• Strong communication to influence decisions and drive growth.

Responsibilities

• Perform business analysis using statistical and predictive modelling techniques.
• Identify analytical requirements and translate into actionable insights for operations.
• Develop reusable analytics solutions to scale insights and avoid duplication.
• Collaborate with clients to deliver ad hoc data and reports.
• Assist in implementing data capture systems and instrumentation.
• Guide junior analysts when appropriate.

Skills

Advanced SQL

Python

Propensity score matching

Difference-in-differences

Synthetic control methods

Generative AI

Experiment design

Data visualization

Statistical modelling

Communication skills

Education

Bachelor's degree in Statistics/Mathematics/Computer Science or related field

Master's degree (preferred)

Tools

Qlik

Amazon QuickSight

Tableau

Plotly Dash

Job description

Data Scientist

Job Description *Only qualified Data Scientist candidates located near San Diego, CA will be considered due to the position requiring an on-site presence * Required Education: Bachelor's in Statistics, Mathematics, Computer Science, or a related field Preferred Education: Master's in Statistics, Mathematics, Computer Science, or a related field Required Skills: Advanced SQL skills and proficiency in visualization tools such as Qlik, QuickSight, Tableau, Plotly Dash (3-5+ years) Strong analytical and modelling skills using Python (for its rich suite of statistical and modelling libraries like NumPy, Pandas, Scikit-learn, etc.) (3-5+ years) Experience with Causal inference techniques such as propensity score matching, difference-in-differences, and synthetic control methods Experience with Generative AI and other evolving technologies to accelerate insights from multi-modal data Ability to formulate data-backed strategies that will drive step-function growth for the business and increase customer benefit Ability to generate hypotheses grounded in customer behaviour, industry trends, and external market factors Experience in designing and interpreting complex experiments beyond traditional A/B testing methods Demonstrated experience in building reusable and scalable analytics solutions, with a focus on efficiency and avoiding duplication of work Outstanding communication skills with the ability to influence decision-makers and build consensus with teams Quick learner, adaptable, with the ability to work independently or as part of a team in a fast-paced environment Preferred Skills: 5+ years of experience in data science or product analytics (preferably in fintech), with a strong foundation in predictive modelling, customer segmentation, and experimentation Duties: Performs business analysis using various techniques, e.g. statistical analysis, explanatory and predictive modelling, data mining Determines best practices and develops actionable insights and recommendations for the current business operations Works directly with the internal or external client to identify analytical requirements May help to produce ad hoc data and reports May assist in implementing or developing systems to capture business operation information May occasionally guide less experienced business data analysts