Must have strong 4 years of hands-on experience with Python or R, SQL, and Tableau
Need Statistician,
Location: Austin, TX n or Elk Grove, CA
Total EXP- 9+ year
NOT Data Scientist
Summary:
We are seeking an experienced Data Scientist with a minimum of 4 years of hands-on experience with Python or R, SQL, and Tableau. The ideal candidate will have a strong background in statistical analysis, causal modeling, and data visualization, with the ability to translate complex data into actionable insights. Excellent communication is essential for this role.
Responsibilities:
- Perform formal statistical analyses, including hypothesis testing, regression, and causal modeling.
- Use SQL for data extraction, transformation, and modeling to prepare datasets for analysis.
- Develop and automate statistical models, conduct exploratory data analysis, and implement machine learning algorithms using Python or R.
- Design and build interactive visualizations in Tableau that effectively communicate insights and drive business decisions.
- Translate complex analytical findings into clear, actionable insights for both technical and non-technical stakeholders.
- Stay current with advancements in statistical techniques and data visualization tools.
Qualifications:
- Excellent verbal and written communication skills.
- Minimum of 4 years of continuous professional experience in data science, with a focus on statistical modeling.
- Proficiency in Python, SQL, and Tableau.
- Strong knowledge of probabilistic, statistical, and regression modeling.
Preferred Qualifications:
- Experience with causal modeling, explanatory machine learning, and model interpretation.
- Experience in a fast-paced, dynamic environment, preferably in information technology.
Please search for a statistician; not a data scientist. A data scientist who specializes in statistical analysis is ok, but I think the most effective way to screen candidates is to find ones who consider themselves a statistician. My goal is to add people to the team who have experience with formal data analysis, which generally entails probabilistic and statistical modeling, experimental design and analysis, causal modeling, and explanatory machine learning. They also need to be proficient with the standard tools, like Python or R, SQL, and Tableau.One of the main challenges I have faced is that most of the contractors I have interviewed equate building data visualizations and dashboards to analysis, when that’s actually just the starting point. Data exploration is essential, but insufficient to derive robust insights. I am looking for someone who has this same perspective and knows how to use the appropriate techniques to derive robust insights.