64 Data Analyst (Lead/Senior) Jobs in San Francisco, CA
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Settle is Hiring a Remote Data Analyst (Lead/Senior)
About the role:
As an early member of the team, you’ll get to be a part of shaping and building our analytics organization. Your strategic insights will be crucial in shaping our risk assessment methodologies and contributing to the overall success of our product.
What you’ll do:
- Partner with our Risk team to drive insights on credit risk factors for potential customers and help determine data-driven underwriting strategies.
- Lead projects to drive insights on customer-level business metrics, such as estimating customer lifetime value.
- Analyze product usage to help us understand our customers better and generate hypotheses on how to improve their experience.
- Help the sales and marketing team optimize their targeting to maximize time spent on the best prospects and understand their impact.
- Find efficiencies in how we can operate better as a team.
- Help other team members do more with our data and drive adoption of our data products
- Define and analyze key metrics for the company, such as customer lifetime value.
What you’ll need:
- 3 years of experience in data analytics, data science or business intelligence role with a Master’s degree in quantitative or technical field (like economics, mathematics, statistics or data science)
- In lieu of Master degree, a Bachelor’s degree and 5 years of experience in data analytics, data science or business intelligence role
- Experience in fintech highly preferred
- Demonstrated experience writing high-quality SQL code
- Proficiency in Python
- Experience with credit risk and income statement analysis
- Explain complicated technical concepts to non-technical stakeholders
- Ability to lead analytics projects
- Curiosity to learn new skills, tools, and subjects
Compensation:
This role has an annual starting salary range of $130,000 - $170,000 equity benefits.
Job level and actual compensation will be decided based on factors including, but not limited to, individual qualifications objectively assessed during the interview process (including skills, prior relevant experience, potential impact, and scope of role).
Job Summary
Full Time
Retail
$120k-157k (estimate)
03/15/2024
04/05/2024
settlescarstrucksrvs.com
FLINT HILL, VA
<25
1997
WILLIAM SETTLE
$50M - $200M
Retail
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The following is the career advancement route for Data Analyst (Lead/Senior) positions, which can be used as a reference in future career path planning. As a Data Analyst (Lead/Senior), it can be promoted into senior positions as a Data Analyst IV that are expected to handle more key tasks, people in this role will get a higher salary paid than an ordinary Data Analyst (Lead/Senior). You can explore the career advancement for a Data Analyst (Lead/Senior) below and select your interested title to get hiring information.
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A data analyst also helps the business use the present data to make better business decisions and deliver better services to consumers.
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Their role will be like to work on collaborative, multidisciplinary teams with leaders where they can review and analyze data and to develop the presentation for the data consumption across the organization.
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Data analysts work constantly with stakeholders, fellow colleagues and data suppliers, so good communication skills are essential.
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Many data analysts are required to create presentations of their findings to share with stakeholders and other key members of an organization.
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Gathered requirements, analyze data and create functional/technical specifications to functionality required by new business rules, regulations or standards change.
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Career tips from people on Data Analyst jobs
Data analysts typically work with existing data to solve defined business problems.
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Data analysts rely on various tools to collect and make sense of their data.
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Banks and financial firms need data analysts for financial reporting and forecasting.
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Data analysts often work directly with more senior data team members like data scientists or data engineers.
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Predictive analysis refers to a data analyst's ability to use data, machine learning and statistical algorithms to predict the likelihood of future outcomes based on previous historical data.
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