Vanguard
DataScientist,Specialist
Neural analysis suggests this role is
optimal for Mid candidates.
“Data Scientist, Specialist at Vanguard. Skills: Data science, Predictive analytics, Statistical modeling, Machine learning. Develop complex queries. Perform extensive programming”
Industry & Context.
Data inconsistencies; Data errors; Data gaps
No visa sponsorship
What They're Looking For.
Must Have
5 years of experience in data science, Expertise in programming with Python, Expertise in programming with R, Hands-on experience with machine learning libraries, Understanding of data pipelines, Understanding of data wrangling, Statistical experience in big data environments, Bachelor’s degree in Analytics, Bachelor’s degree in Applied Mathematics, Bachelor’s degree in Economics, Bachelor’s degree in Statistics, Bachelor’s degree in Computer Science, Master’s degree in a quantitative field, Diploma in a quantitative field
Nice to Have
PhD preferred, Specific ML framework experience, Cloud platform certs
What You'll Do.
Develop complex queries
Perform extensive programming
Prepare data for modeling
Lead deep dive diagnostics
Execute deep dive diagnostics
Lead predictive analytics
Execute predictive analytics
Lead prescriptive analytics
Execute prescriptive analytics
Mentor junior data scientists
Develop junior data scientists
Mentor junior analysts
Develop junior analysts
Identify data inconsistencies
Diagnose data inconsistencies
Document data assumptions
Forage to fill data gaps
Engage with internal stakeholders
Understand business processes
Probe business processes
Bring structure to requests
Translate requirements into analytic approach
Guide research design
Guide model validation
Provide statistical consultation
Serve as analytics expert
Contribute to analytic community growth
Prepare insight presentations
Deliver insight presentations
Communicate analytical findings
Communicate analytical implications
Participate in special projects
Design scalable data mining models
Design reporting protocols
Apply data science techniques
Solve business problems
Contribute to analytics advancement
Conduct exploratory research
Apply statistical theory
How You'll Work.
Team & Collaboration
Cross functional teams; Analytic community
Communication Scope
Insight presentations; Action recommendations; Complex findings
Full Job Description
**Responsibilities:** * Develops complex queries and performs extensive programming to access, transform, and prepare data for statistical modeling. * Leads and executes deep dive diagnostic, predictive, and prescriptive analytics to support data-driven business decision making. Mentors and develops junior data scientists and analysts. * Identifies and diagnoses data inconsistencies and errors, documents data assumptions, and forages to fill data gaps. * Engages with internal stakeholders to understand and probe business processes in order to develop hypotheses. Brings structure to requests and translates requirements into an analytic approach. * Guides test design, research design, and model validation. Provides statistical consultation services. Serves as the analytics expert on cross functional teams for large strategic initiatives and contributes to the growth of the Vanguard analytic community. * Prepares and delivers insight presentations and action recommendations. Communicates complex analytical findings and implications to business leaders. * Participates in special projects and performs other duties as assigned. * Designs scalable data mining models and reporting protocols to identify trends and patterns in massive datasets. * Applies modern and emerging data science techniques to solve business problems across functions such as marketing, economics, and operations. * Contributes to the advancement of analytics through exploratory research and application of cutting-edge statistical theory. **Qualifications:** * Minimum 5 years of experience in data science, predictive analytics, or advanced statistical modeling roles * Expertise in programming with Python, R, or SQL; hands-on experience with machine learning libraries (e.g., Scikit-learn, TensorFlow); strong understanding of data pipelines, data wrangling, and statistical techniques; experience in big data environments (Spark/Hadoop); familiarity with visualization tools like Tableau or Power BI * Bachelo
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