Senior Data Scientist

Senior Data Scientist Agivant Technologies INC Sherman Oaks, CA Job Details Full-time $120,000 - $150,000 a year 3 hours ago Benefits Health insurance Dental insurance Vision insurance Qualifications Performance dashboard reports Looker Dashboard development Power BI Bayesian inference Data visualization software proficiency Hypothesis testing Cloud data warehouses NumPy Mid-level Marketing mix modeling Tableau ROI Snowflake SQL Pandas Outlier detection Attribution modeling Decision making Data quality monitoring Statistical modeling Mentoring Matplotlib Data interpretation Experimental design Developing data pipelines Seaborn Presentation creation A/B testing Data validation Linear regression Root cause analysis Redshift Machine learning libraries Cross-functional collaboration Research findings presentation Model evaluation Data-driven decision making BigQuery Communication skills Data warehouse Project stakeholder communication Python Cross-functional communication Stakeholder management Database software proficiency Full Job Description Role Overview We are looking for a Mid‑Level Data Scientist who is passionate about turning data into actionable business insights. This role sits at the intersection of data analysis, statistical modeling, and business decision‑making . You will work closely with stakeholders across Product, Marketing, Engineering, and Leadership to design models, monitor performance, and influence strategy through data. The ideal candidate can independently own data problems end‑to‑end—from understanding the business context, exploring data, building models, and communicating insights clearly. Key Responsibilities Analytics & Modeling Analyze large, structured time‑series datasets to uncover trends, correlations, and causal signals. Build and evaluate statistical and machine learning models such as: Regression models (linear, regularized) Time‑series and seasonality models Classification and anomaly detection models Apply concepts of incrementality, attribution, and ROI analysis to quantify impact. Design experiments or quasi‑experiments (A/B testing, pre‑post analysis, causal inference). Business Problem Solving Translate ambiguous business questions into well‑defined analytical problems. Partner with stakeholders to identify key metrics, assumptions, and success criteria. Distinguish between correlation and causation when presenting insights. Provide clear, data‑backed recommendations that influence decisions. Monitoring & Automation Develop automated monitoring systems for core KPIs (e.g., revenue, spend, conversions). Identify and flag statistically significant deviations while minimizing false positives. Incorporate seasonality, trends, and known events into analytical logic. Support root‑cause analysis when anomalies or performance drops occur. Data Engineering & Tooling Write efficient, production‑ready SQL and Python code. Work with data pipelines, data warehouses, and dashboards. Ensure data quality through validation, sanity checks, and documentation. Collaborate with Data Engineers to improve data availability and reliability. Communication & Collaboration Communicate findings clearly to both technical and non‑technical audiences. Create concise presentations, dashboards, and written summaries. Review peers' analyses and models; contribute to best practices within the team. Mentor junior analysts or data scientists where needed. Required Skills & Qualifications Technical Skills Strong proficiency in Python (pandas, numpy, scikit‑learn, statsmodels). Solid SQL skills for querying and transforming large datasets. Good understanding of statistics : Hypothesis testing Confidence intervals Regression analysis Bias, variance, and assumptions Experience working with time‑series data and seasonality. Familiarity with data visualization tools (e.g., matplotlib, seaborn, Tableau, Looker, Power BI).

Conceptual Understanding Clear understanding of:

Correlation vs causation Incrementality and attribution concepts Model evaluation and validation Ability to reason through tradeoffs in modeling choices. Soft Skills Strong problem‑solving and critical‑thinking abilities. Comfortable working with ambiguity and incomplete data. Clear written and verbal communication skills. Curiosity, ownership mindset, and bias toward action. Good to Have Experience with marketing, e‑commerce, fintech, or growth analytics.

Exposure to:

Media Mix Models (MMM) Bayesian modeling Anomaly detection techniques Experience with cloud data platforms (BigQuery, Redshift, Snowflake). Familiarity with workflow orchestration or production monitoring.

Job Type:

Full-time Pay:

$120,000.00 - $150,000.00 per year

Benefits:

Dental insurance Health insurance Vision insurance

Work Location:

In person