The Data Scientist role at Thrivent represents a significant step forward in the data science career ladder, designed for professionals who combine deep technical expertise with a strong understanding of business applications. In this pivotal role, a Data Scientist will lead medium to complex data projects, applying advanced analytical techniques, predictive modeling, and machine learning algorithms to deliver actionable business insights, providing mentorship to junior colleagues while also collaborating with senior team members on strategic projects. This position demands a higher level of autonomy in data exploration, analysis, and solution implementation, requiring not only technical acumen but also the ability to understand and align with the company’s business goals. The Data Scientist’s contributions will be key in driving data-informed decisions, influencing business strategies, and shaping the data science culture within the organization. This role is ideal for individuals with specialized strengths in data processing and feature engineering for ML workflows or marketing attribution modeling, bringing advanced domain knowledge into enterprise-level modeling initiatives.

DUTIES & RESPONSIBILITIES:

The Data Scientist independently manages and leads a range of data science projects, applying advanced critical thinking and technical skills to both simple and complex challenges. This role involves not only executing projects but also conceptualizing and driving project strategies, including comprehensive documentation, and effectively communicating with stakeholders at various levels.

In this role, the Data Scientist is expected to have mastered the essential skills and problem-solving techniques in data science. They are expected to provide:

Advanced Business Problem Analysis and Solution Development: Independently lead the analysis of complex business challenges, developing and proposing sophisticated data-driven solutions. This involves not just collaboration, but also steering projects and driving decision-making processes.
Comprehensive Data Collection and Preprocessing: Independently manage and optimize the collection and preparation of diverse data sources, employ advanced data integration, feature engineering, and pipeline design techniques to prepare high-quality data for modeling and analysis at scale, ensuring data quality and suitability for complex analysis.
In-Depth Exploratory Data Analysis (EDA): Perform advanced EDA to extract deep insights, using more sophisticated statistical methods and visualization techniques. Lead the narrative in translating these analyses into actionable business strategies.
Hypothesis Testing and Advanced Model Validation: Independently conduct and oversee complex hypothesis testing and model validation, utilizing a variety of techniques to ensure robustness and reliability of models.
Leading Predictive Modeling Efforts: Take a lead role in developing and implementing advanced predictive models. Apply cutting-edge machine learning algorithms—including marketing attribution and optimization models—to solve critical business problems, particularly in areas like media mix modeling and channel effectiveness.
Strategic Insights Generation and Reporting: Generate strategic insights that influence business decisions. Lead the preparation and presentation of detailed reports and analyses to stakeholders, showcasing the impact of data science on business outcomes.
Direct Stakeholder Engagement and Relationship Management: Take a proactive role in engaging with business stakeholders. Lead discussions, understand and manage expectations, and independently handle client relationships and project requirements.
Applied Critical Thinking in Business Context: Utilize critical thinking to not only understand but also challenge and refine business strategies. Lead the application of data science methodologies to drive innovative solutions.
Leadership in Learning and Skill Development: Stay at the forefront of emerging trends in data science, machine learning and regulatory requirements. Lead internal training sessions and knowledge-sharing initiatives to elevate the team's capabilities.
Ownership of Data Science Initiatives: Take ownership of significant data science projects within the company. Drive innovative strategies and solutions, showcasing leadership and a deep understanding of the company's goals and challenges.
Model Governance and Regulatory Compliance: Stay informed of the latest regulatory trends and governance practices in modeling, machine learning, and artificial intelligence. Apply this knowledge to ensure that all models are developed and maintained in compliance with relevant laws and industry standards, contributing to the organization’s adherence to best practices and ethical guidelines.

QUALIFICATIONS & SKILLS:

Required:

Experience & Education:

Bachelor’s degree in Data Science or a related quantitative field such as Statistics, Mathematics, Computer Science.
3-5 years of relevant experience in data science or a closely related field. This experience should include hands-on work with data analysis, statistical modeling, machine learning, and delivering actionable insights from data.

Technical Skills

Advanced Programming: Proficiency in data science languages, predominantly Python, with an emphasis on writing production-ready code and a solid understanding of code efficiency and scalability.
Data Manipulation Tools: Experience with data manipulation and analysis libraries (e.g., Pandas, NumPy in Python).
Data Architectures: Deep experience working with both structured and unstructured datasets.
Database Management: Strong skills in managing, processing, and analyzing large datasets. Advanced knowledge of SQL databases.
Data Preprocessing: Skills in cleaning and preparing data for analysis, including dealing with missing data, outliers, and data transformation.
Statistical Analysis and Machine Learning: Deep understanding of statistical methods and machine learning algorithms. Ability to develop, tune, and implement models independently.
Data Visualization: Expertise in creating insightful visualizations and interactive dashboards, using tools like Tableau, Power BI, or advanced libraries in Python like Matplotlib, Seaborn, Bokeh, plotly (Python).
Big Data Technologies: Experience with big data tools and frameworks like Spark or similar technologies.
Model Deployment and MLOps: Knowledge of model deployment, monitoring, and maintenance. Familiarity with MLOps practices and tools, such as Databricks, SnowFlake, SageMaker, Kubeflow, mlflow, etc.

Analytical Skills

Complex Problem-Solving: Ability to tackle complex data problems and devise effective solutions.
Critical Thinking: Skilled in evaluating data and analytics from multiple perspectives to derive the most value.
Hypothesis Testing: Strong skills in designing and executing robust tests for data models and hypotheses.
Research and Development: Capability to conduct research for innovative data solutions and apply findings to business problems.

Soft Skills

Effective Communication: Proficient in communicating complex data insights to both technical and non-technical stakeholders.
Collaboration and Teamwork: Ability to work collaboratively with cross-functional teams and lead project segments.
Leadership Qualities: Aptitude for mentoring junior team members and leading project initiatives.
Adaptability and Continuous Learning: Eagerness to stay updated with the latest data science trends and technologies and adapt to evolving business needs.
Time Management: Skills in managing time effectively, especially when handling multiple tasks or projects.

Preferred:

Domain Knowledge: Understanding of the financial services and insurance products that Thrivent operates in.
Project Management: Basic project management skills to oversee data projects from conception to delivery, leveraging frameworks such as Agile methodology.
Version Control: Proficiency in using version control systems, such as Git.
Education: Master’s degree or PhD in a quantitative field.

Pay Transparency

Thrivent’s long-term growth depends on attracting, rewarding, and retaining people who are committed to helping others thrive with purpose. We accomplish this by offering a wide variety of market competitive compensation programs to attract, reward, and retain top talent. The applicable salary or hourly wage range for this full-time role is $118,105.00 - $159,788.00 per year, which factors in various geographic regions. The base pay actually offered will be determined by a variety of factors including, but not limited to, location, relevant experience, skills, and knowledge, business needs, market demand, and other factors Thrivent deems important.

Thrivent is unique in our commitment to helping people to be wise with money and live balanced and generous lives. That extends to our benefits.

The following benefits may be offered: various bonuses (including, for example, annual or long-term incentives); medical, dental, and vision insurance; health savings account; flexible spending account; 401k; pension; life and accidental death and dismemberment insurance; disability insurance; supplemental protection insurance; 20 days of Paid Time Off each year; Sick and Safe Time; 10 paid company holidays; Volunteer Time Off; paid parental leave; EAP; well-being benefits, and other employee benefits. Eligibility for receipt of these benefits is subject to the applicable plan/policy documents. Thrivent’s plans/policies are subject to change at any time at Thrivent’s discretion.

Thrivent provides Equal Employment Opportunity (EEO) without regard to race, religion, color, sex, gender identity, sexual orientation, pregnancy, national origin, age, disability, marital status, citizenship status, military or veteran status, genetic information, or any other status protected by applicable local, state, or federal law. This policy applies to all employees and job applicants.

Thrivent is committed to providing reasonable accommodation to individuals with disabilities. If you need a reasonable accommodation, please let us know by sending an email to human.resources@thrivent.com or call 800-847-4836 and request Human Resources.

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