Sr Data Scientist - Data Scientist Advisor candidates will join a team focused on enterprise analytics and statistical modeling to solve complex business problems. The role involves leading cross-functional teams, mentoring junior staff, and managing high-complexity projects from initial concept to production. Responsibilities include performing qualitative and quantitative analyses, such as clustering, regression, and sentiment analysis, while designing reporting dashboards and whitepapers for leadership. Candidates must be proficient in Python, Scala, R, C++, or Java, alongside SQL and ETL concepts. The technical stack includes machine learning frameworks like SKLearn, XGBoost, TensorFlow, and PyTorch, with data tools such as Databricks, Spark, Kafka, Hive, and Hadoop. Experience with cloud environments like Azure or AWS and visualization tools including Tableau, Spotfire, and Power BI is required to provide actionable insights from vast quantities of disparate data.
Develop and execute end-to-end data solutions from initial concept to production.
Perform complex predictive modeling, statistical analysis, and machine learning to drive business decisions.
Conduct both qualitative and quantitative analyses on large datasets to identify trends and insights.
Design and implement reporting dashboards to visually communicate key metrics to stakeholders.
Mentor junior staff and lead cross-functional teams through complex projects.
Advise senior leadership on data strategy, emerging technologies, and actionable business recommendations.
Author whitepapers and present technical data science topics at industry conferences.
Collaborate with IT departments to integrate new tools and stay current with industry trends.
What we're looking for
Bachelor's degree in data science, computer science, applied mathematics, statistics, or a related quantitative field.
Five years of experience in measurement and analysis, quantitative problem solving, operations analysis, marketing analysis, simulation, or predictive analytics.
Seven years of experience for the Advisor role in applying data science techniques to solve analytics problems.
Proficiency in programming languages including Python, Scala, R, C++, and Java.
Experience with machine learning frameworks such as SKLearn, XGBoost, TensorFlow, PyTorch, and MLlib.
Proficiency with data tools like Spark, Kafka, Hive, Hadoop, Databricks, and MLFlow.
Expertise in SQL, ETL concepts, query performance tuning, and visualization tools like Tableau, Spotfire, or Power BI.
Proven leadership skills and the ability to communicate complex technical information to diverse audiences.