Location: US Remote

Reports To: Director of Data and Analytics 

Salary Range: $130,000 - $170,000

Position Summary:

The Data Engineer is a core builder on IEM’s data and analytics team. This role develops and maintains the data pipelines and transformation models that power Tableau dashboards and business decisions across the organization. Working within an established modern data stack (Fivetran, Snowflake, dbt, Tableau. The Data Engineer turns raw source data into reliable, well-tested, and well-documented analytics-ready datasets. This is a hands-on individual contributor role with real ownership of production data models and growing influence on engineering standards.

Ideal Candidate Profile

You have 3–5 years of experience building data pipelines and transformation workflows in cloud environments. You’re proficient with SQL and Python, comfortable working in Snowflake, and have hands-on experience with dbt or similar transformation tools. You write clean, tested code and take pride in documentation. You’re curious about the business context behind the data and can translate stakeholder questions into well-modeled datasets. You work well on a small team, take feedback constructively, and are eager to grow your skills in analytics engineering, data modeling, and cloud data architecture. You’re excited about AI’s role in modern data work and comfortable using AI coding assistants and agents to accelerate your output.

Key Responsibilities:

• Data Pipeline Development: Build and maintain ELT pipelines using Fivetran and custom integrations that ingest data from source systems including Procore, Salesforce, ERP platforms, and internal databases into Snowflake
• dbt Transformation Models: Develop, test, and document dbt models that transform raw data into clean, reliable datasets for analytics and reporting across Finance, Production, Supply Chain, and Engineering
• Data Modeling: Build dimensional models and staging layers following team conventions, ensuring data is structured for optimal Tableau dashboard performance and ad-hoc analysis
• Data Quality: Write and maintain dbt tests, monitor data freshness, and investigate data quality issues when they arise, owning resolution through to root cause
• Source System Integration: Work with APIs and data connectors to integrate new data sources, troubleshoot ingestion issues, and ensure reliable data flow into the warehouse
• Documentation: Maintain clear documentation for data models, pipeline configurations, and business logic so the team can understand and extend your work
• Collaboration: Partner with business stakeholders to understand data needs, clarify requirements, and deliver datasets that answer real operational questions
• Performance: Monitor query performance and pipeline efficiency, identifying opportunities to optimize warehouse costs and model run times
• Engineering Standards: Participate in code reviews, follow Git workflows and CI/CD practices, and contribute to improving the team’s development processes
• Continuous Learning: Stay current with modern data stack tools and practices, bringing ideas for improvement back to the team
• AI-Assisted Development: Use AI coding assistants and agent-based tools to accelerate pipeline development, code generation, testing, and documentation. Manage AI agents as part of your daily workflow to increase throughput and quality

Qualifications:

• Bachelor’s degree in Computer Science, Information Systems, Data Science, or related field, or equivalent experience
• 3–5 years of experience in data engineering, analytics engineering, or BI development with hands-on experience building production data pipelines
• Strong SQL skills including CTEs, window functions, complex joins, and query optimization
• Experience with Snowflake or similar cloud data warehouses
• Working experience with dbt (data build tool) for building and testing data transformation workflows
• Proficiency in Python for data processing, scripting, and API integrations
• Experience with data integration platforms such as Fivetran or similar ELT tools
• Familiarity with Tableau or similar BI tools and understanding of how data structure impacts dashboard performance
• Comfortable with Git version control and modern development workflows including code review and CI/CD
• Strong problem-solving skills with ability to debug data issues systematically
• Clear written and verbal communication skills with ability to document work and explain technical concepts to non-technical stakeholders
• Self-motivated with ability to work independently in a remote environment while collaborating across a distributed team
• Experience using AI coding assistants (e.g., Claude, GitHub Copilot) and comfort directing AI agents to perform data engineering tasks such as writing SQL, generating dbt models, and debugging pipeline issues
• Preferred: Experience with manufacturing, construction, or project management data systems such as Procore, ERP platforms, or supply chain tools
• Preferred: Familiarity with dimensional modeling concepts (star schemas, fact/dimension tables)

Location

Fully remote within the United States. May require up to 10% travel to IEM facilities for team collaboration, project kickoffs, and stakeholder meetings. 

Senior Manager, Data Science

Portfolio Management and Loss Mitigation

The Role: 

SoFi is seeking an inspirational and deeply experienced Senior Manager to lead the Portfolio Management and Loss Mitigation function in our Risk Data Science team. Reporting to the Head of Risk Data Science, this role will lead the development, deployment, and governance of portfolio management and loss mitigation models for all credit products.

The ideal candidate is a hands-on leader who can transition the team from traditional modeling to next-generation machine learning platforms, leveraging emerging data sources (e.g., cash flow, alternative bureaus) to significantly improve portfolio performance, reduce losses, and ensure rigorous adherence to Model Risk Management (MRM) standards. This role requires exceptional organizational leadership, an ability to influence stakeholders, and proven success in delivering complex models into a regulated production environment.

What You'll Do: 

• Portfolio Management and Loss Mitigation Excellence: Directly oversee the development and deployment of Next Generation models designed to manage and mitigate portfolio losses while maintaining loss guardrails.
• Drive Next-Generation Capabilities: Incorporate industry trends and advanced techniques (NLP, Graph Mining, LLMs, Deep Learning) to solve complex, high-impact risk problems where established principles may not fully apply.
• Alternative Data Strategy: Spearhead the evaluation and integration of alternative data sources (Macro-Economic variables, tri-bureau, LexisNexis, cash flow data) to enhance predictive power across all credit products.
• Lead the current team of high-performing Staff and Senior Data Scientists. Recruit, mentor, and foster talent through deliberate interactions, succession planning, and creating a high-accountability, low-ego culture.
• Model Risk Management (MRM): Act as the primary owner for all models in the portfolio, ensuring robust documentation, monitoring, and successfully navigating the 2nd Line of Defense (2LOD) review and approval process (SR 11-7 familiarity is mandatory).
• Stakeholder Alignment: Interact and negotiate with senior management and external stakeholders to reconcile competing views and drive critical, high-impact business decisions.
• Automation and Efficiency: Lead efforts to automate model monitoring and governance processes to create scalable and auditable infrastructure.

What You'll Need:

• Experience: 8+ years of progressive experience in credit risk, modeling, and data science within a regulated financial institution (FinTech, Bank, or similar), with at least 3 years in a people management role, managing technical staff.
• Education: Master’s or Ph.D. degree in a quantitative field (Statistics, Computer Science, Engineering, Operations Research, etc.).
• Technical Acumen: Deep expertise in advanced statistical and machine learning modeling techniques (e.g., Gradient Boosting, Deep Learning, Causal Inference).
• Regulatory Knowledge: Detailed working knowledge of model risk management standards (e.g., SR 11-7) and the ability to operate within a highly regulated environment.
• Tools & Platforms: Expert-level proficiency in Python (PySpark, scikit-learn, TensorFlow/PyTorch) and SQL/data warehouse technologies (e.g., Snowflake, Hive). Familiarity with modern MLOps platforms and cloud computing (AWS).
• 3+ years of progressive people management experience is required, including the ability to recruit, mentor, and foster talent within a team of high-performing Staff and Senior Data Scientists.
• Communication: Ability to distill highly complex analytical concepts into clear, concise, and compelling narratives for non-technical leadership.

The role:

We are seeking a Senior Financial Systems Analyst who will support Workday on a day-to-day basis focusing on unlocking its vast reporting possibilities. This is an exciting role for someone to make a direct impact at SoFi by shaping our processes and providing reporting solutions to help drive visibility, while also playing a key role in our implementation of Workday Financials.

Success in this role hinges on your technical aptitude, quantitative abilities, and business acumen: You are an expert in Workday Financials and also understand data flows/SQL/Tableau, while also having the ability to step back and understand the business needs. You treat stakeholders as a partnership – you are there at each step of the way and you know that we only succeed if we succeed together.

This position will be part of the Business Intelligence and Systems team within Accounting Controllership.

What you’ll do: 

• Support Workday Financials through configuration of business process, condition rules, validations
• Create and maintain complex Workday financial reports
• Participate in bi-annual Workday release regression testing and uptake of new features.
• Stay updated on the Workday roadmap and propose changes and solutions in areas of focus.
• Act as a technical expert and support the broader finance team in Workday reporting
• Develop strong collaborative relationships with the Finance, Engineering, People orgs and across the company, with a specific focus on our Workday integrations
• Leverage Workday and other tools and systems to design, develop & deliver robust and scalable reporting
• Perform daily administrative and production support tasks as required
• Develop and deliver training on SoFi’s financial business processes and use of Workday
• Be part of a great team, but capable of operating independently - managing relationships, deliverables and expectations with your business partners
• Be personable, approachable and able to connect with each and every person on the team and throughout the business
• Remain detail-oriented while working across a variety of projects

Who are you:

• Demonstrated ability to work collaboratively across different functions and effectively influence senior business partners
• Expert in Financial Management Systems, with an understanding/vision of how to architect the perfect solution
• Experience with Database Management systems (SQL) who enjoys solving complex problems
• Experience with front-end reporting tools (Tableau)
• Strong ability to project manage and to remain detail-oriented while working with numerous stakeholders
• Strong analytical, problem solving and critical thinking skills
• High EQ with ability to influence outcomes and communicate technical content to general audiences
• Knowledge of the banking space a strong plus

What you’ll need:

• Bachelor's degree required, preferably in Mathematics, Computer Science, Statistics or a Business related degree (Masters a plus)
• 5+ years of work experience
• 2 + years of experience configuring and supporting a combination of at least 2 of the following modules: Supplier accounts, Customers, Projects and Billing, Business Assets, Expenses,  Banking and Settlement, Financial Accounting and Accounting Center
• Subject matter expert on:
• Workday Financial Reporting (Advanced, Matrix)
• At least one of the modules: Supplier Accounts, Customers
• Experience required:
• Multiple subsidiary structure and working with different functional currencies
• ETLs/ELTs related to Workday integrations
• SOX Compliance
• Experience preferred:
• Workday Pro Certifications
• Workday Financial Reporting (Composite, Discovery Boards, Prism, Office Connect)
• Consolidations
• FDM design, deployment, and maintenance
• SQL (Snowflake)
• Tableau
• Finance planning tools (ex: Planning analytics (TM1))
• Alteryx
• Integration platforms such as Fivetran or Mulesoft
• Jira / Confluence  or other Scrum Management tools
• Strong verbal and written communication skills
• Spanish fluency a plus
• Demonstrated ability to work collaboratively across different functions and effectively influence senior business partners

Shape a brighter financial future with us.

Together with our members, we’re changing the way people think about and interact with personal finance.
We’re a next-generation fintech company using innovative, mobile-first technology to help our millions of members
reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re
proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values
guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.

The Role

The Fraud Program is seeking a Staff Risk Analyst to lead data governance initiatives, analytics, and reporting across
the Fraud Center of Excellence (CoE). This role will serve as a key partner in developing, maintaining, and enhancing
fraud KPIs, KRIs, dashboards, and enterprise risk reporting to enable data-driven decision making and effective fraud
risk oversight.

The Staff Risk Analyst will play a critical role in ensuring data integrity, consistency, and transparency across fraud
metrics, while delivering actionable insights into fraud performance, emerging risks, and operational effectiveness
across all products and fraud domains.

This role will partner closely with Fraud Strategy, Operations, Risk, Data, and Business Intelligence teams to build
scalable analytics solutions, standardize metric definitions, and improve enterprise-wide visibility into fraud risk.
The ideal candidate will bring a strong technical data background, experience in risk analytics, and a passion for
building scalable data and reporting frameworks within a fast-paced fintech environment. Additionally, the
candidate will also have strong proficiency in SQL, Python, Snowflake, and Tableau. You’ll need to be a self-motivated
leader with the ability to drive cross-functional collaboration between all lines of business. IIf you love working with
data and have a passion for doing the right thing, we want to hear from you!

What you’ll do:

Fraud Data Analytics, Insights, and Data Governance (Primary Focus)
● Analyze fraud data across products and channels to identify trends, anomalies, and emerging fraud risks.
● Develop data-driven insights and recommendations to support fraud strategy, operations, and risk
management decisions.
● Partner with cross-functional teams to translate business problems into analytical solutions that improve
fraud detection, prevention, and member experience.
● Establish and enforce data governance standards for fraud metrics- including data definitions, lineage, and
controls; and effectively leading a strategic data governance council cross-functionally.
● Identify and resolve data quality, consistency, and availability issues impacting fraud reporting and
analytics.
● Partner with Data Engineering and BI teams to ensure reliable, scalable, and well-documented data
sources.
KPI / KRI Framework & Performance Monitoring
● Support the design, development, and ongoing enhancement of Fraud KPIs, KRIs, and Risk Appetite

Statement (RAS) metrics across the Fraud CoE.

● Ensure consistent metric definitions, calculations, and reporting methodologies across business units.
● Monitor metric performance and provide insights into drivers of variance, trends, and risk signals.
Dashboarding & Reporting
● Assist in designing, building, and maintaining Tableau dashboards and automated reporting solutions to
provide real-time visibility into fraud performance.
● Deliver executive-level reporting and visualizations for fraud governance committees and leadership.
● Improve reporting efficiency through automation and scalable data pipelines (e.g., Snowflake), where
needed, in partnership with our risk analytics and data teams
Fraud Risk Management & Assessment Support
● Support Fraud Risk Self-Assessments (FRSA) and other risk evaluation activities through data analysis and
metric development.
● Assist in identifying key risk drivers and areas of elevated fraud exposure across products and processes.
● Provide analytical support for audit, regulatory, and risk management requests.
Cross-Functional Collaboration & Program Support
● Collaborate with Fraud Strategy, Operations, and Program teams to align data, metrics, and reporting with
business needs.
● Support broader Fraud Program initiatives and analytics projects as needed, including strategy
performance analysis and operational insights.

What you’ll need:

● 4+ years of experience in data analytics, fraud analytics, or risk analytics within financial services, fintech, or
banking.
● Strong experience working with large datasets and relational databases.
● Advanced proficiency in SQL and experience with Snowflake or similar data platforms.
● Experience building dashboards and data visualizations (Tableau preferred).
● Strong understanding of KPI/KRI frameworks, performance metrics, and risk monitoring concepts.
● Experience with data governance, data quality management, or metric standardization.
● Strong analytical and problem-solving skills with the ability to translate complex data into actionable
insights.
● Excellent communication skills, with the ability to present findings to both technical and non-technical
stakeholders.
● Ability to work cross-functionally and manage multiple priorities in a fast-paced environment.
● Proficient in other programming and data analysis tools such as Python, R, or SAS.

Nice to Have:
● Advanced degree in Data Science or Machine Learning.
● Experience in implementing or overseeing AI/ML-based models for fraud detection
● Experience working in or working closely with model risk management is a plus.