Actuarial Data Scientist (FCAS)
for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. No job title heading. No Job ID. Remove boilerplate. Must preserve all substantive info.
We need to parse the posting.
Let's extract sections:
- About the role / company description: "We are looking for an FCAS to join the American Modern Predictive Analytics team as a Principal Data Scientist and play a key leadership role in advancing pricing model strategy. American Modern Insurance Group, Inc., a Munich Re company, is a widely recognized specialty insurance leader that delivers ...". That's about the role/company.
- Responsibilities: list of duties under "Roles & Responsibilities:" many bullet-like sentences.
- Requirements: maybe "Required Technical Skills:" and "Skills / Knowledge / Experience:" and "Education, Certifications & Designations:" could be considered Requirements/Qualifications.
- Qualifications: maybe combine.
- Skills: maybe separate.
- Benefits: list of benefits.
- Pay: not mentioned.
- Schedule: not mentioned.
Thus we will have sections: About the role, Responsibilities, Requirements (maybe combine Required Technical Skills, Skills/Knowledge/Experience, Education...), Benefits.
We must not create Pay or Schedule sections because not present.
We need to use for each section heading. Use - for any list of duties/requirements/benefits. Use
for prose.
We must preserve all substantive info, not invent or summarize away detail. Must not include boilerplate like EEO, equal opportunity, scam warning, etc. Also remove duplicated lines.
We need to be careful to keep all substantive details.
Let's extract substantive content.
First paragraph: "We are looking for an FCAS to join the American Modern Predictive Analytics team as a Principal Data Scientist and play a key leadership role in advancing pricing model strategy. American Modern Insurance Group, Inc., a Munich Re company, is a widely recognized specialty insurance leader that delivers products and services for residential property – such as manufactured homes and specialty dwellings – and the recreational market, including boats, personal watercraft, classic cars, and more. We provide specialty product solutions that cover what the competition often can’t. We write admitted products in all 50 states and have a premium volume of $2.2 billion. Headquartered in Amelia, Ohio, and with associates located across the United States, we are part of Munich Re’s Global Specialty Insurance division. Our employees receive boundless opportunity to grow their careers and make a difference every day - all in a flexible environment that helps them succeed both at work and at home."
That's about the role/company.
Next: "As a senior technical leader, you will drive the end-to-end development, enhancement, maintenance, and monitoring of personal lines pricing models. This role is highly visible and influential. While it does not include direct people management, it requires strong technical modeling skills, ownership of regulatory filings and objections, and mentorship of junior data scientists and analysts. As you grow in this role, the opportunity will extend beyond pricing, enabling you to contribute to broader predictive and decision science initiatives that support long-term enterprise purpose."
Actually there is "Purpose: Use data and statistical analysis to drive business decisions and target improved results across various functional areas." That's a purpose statement.
Then "Roles & Responsibilities:" followed by many sentences each maybe separate bullet.
Let's list them:
- Lead pricing model strategy for a subset of products.
- Develop, deploy, monitor, and maintain predictive models.
- Effectively collaborate with stakeholders.
- Manage filing schedules for aligned products.
- Prepare and complete predictive analytics analysis and modeling with guidance on very complex projects.
- Participate in the development of predictive analytics and modeling presentations and present results/topics to customers (internal & external) and management as requested.
- Concentrate on loosely defined problems which require application of creative approaches.
- Contribute to projects that yield actionable insights the business can use to increase customer satisfaction, policy growth, retention, and profitability.
- Complete required data preparation, including data input with guidance.
- Identify data anomalies and seek guidance on necessary adjustments.
- Identify data and operational issues requiring specialized analytics attention, data scrubbing, and modeling techniques.
- Document and communicate assumptions, results, and alternatives to team members and internal customers with guidance.
- Communicate with regulators when called upon to support rate filings or modeling practices in general.
- Create and maintain modeling best practices and new techniques in coordination with internal and external business partners.
- Explain advanced analytic and modeling procedures in the language that audiences with no predictive analytics training can easily find connections to.
- Understand customers' requests and hidden issues and explain possible solutions in their language.
- Schedule and prioritize workload demands.
- Maintain very good organization skills.
- Complete technical peer reviews as needed.
- Maintain strong interpersonal skills - listen deeply, ask correct questions, take notes, complete professional oral and written business communications (including email communications), presentations, and build business relationships in order to better understand insurance company processes and functions.
- Established relationships with multiple areas of interaction.
- Mentor junior data scientists and team members.
That's a lot.
Then "Required Technical Skills:" list:
- FCAS required.
- Experience in multiple programming languages, including R and Python.
- Deep understanding of GLMs and GBMs.
- Familiarity with AI and machine learning concepts, including supervised and unsupervised learning, deep learning, and natural language processing.
- Experience with Databricks or similar big data platforms is highly desirable.
- Strong understanding of data structures, algorithms, and software design patterns.
- Experience working in an agile team environment, with familiarity with Scrum or Kanban methodologies.
- Strong commitment to testing, validation, and continuous improvement of models and workflows.
- Proven experience with project management and prioritization.
Then "Skills / Knowledge / Experience:" list:
- Independently build models and statistical analyses.
- Effectively communicate results to business partners and help drive business decisions.
- Participate in creation and discussion of best practices and propose new techniques.
- Manage projects and direct work of more junior team members.
- Six (6) or more years of data science/predictive analytics experience in insurance or eight (8+) or more years predictive modeling experience in another industry.
Then "Education, Certifications & Designations:" list:
- Master’s degree in Business Analytics, Statistics, Computer Science, or Statistics/Math and Economics double major, or Statistics/Math and Computer Science double major or Statistics/Math and Operation Research double major.
Then benefits: "We are proud to offer our employees, their domestic partners, and their children, a wide range of insurance benefits:" then list:
- Two options for your health insurance plan (PPO or High Deductible)
- Supplemental Life and AD&D plans that you can purchase for yourself and dependents (includes spouse/domestic partner and children)
- Voluntary Benefit plans that supplement your health and life insurance plans (Accident, Critical Illness and Hospital Indemnity)
- Prescription drug coverage (included in your health insurance plan)
- Short and Long Term Disability coverage
- Vision and dental insurance plans
Then "In addition to the above insurance offerings, our employees also enjoy:" list:
- A robust 401k plan with up to a 5% employer match
- A retirement savings plan that is 100% company funded
- Paid time off that begins with 24 days each year, with more days added when you celebrate milestone service anniversaries
- Eligibility to receive a yearly bonus as a Munich Re employee
- A variety of health and wellness programs provided at no cost
- A hybrid environment that gives you a choice in where and how you get work done
- A corporately subsidized on-site cafeteria as well as a We Proudly Serve coffee shop
- An on-site complimentary workout facility as well as walking trails on campus grounds
- On-site wellness center complete with nurse practitioner
- Financial assistance for adoptions and infertility treatment
- Paid time off for eligible family care needs
- Tuition assistance and educational achievement bonuses
- Free parking
- A corporate matching gifts program that further enhances your charitable donation
- Paid time off to volunteer in your community
Then after that there is Diversity and Inclusion statement, EEO, etc which we should remove as boilerplate.
Also there is "Sometimes we are fortunate enough to receive a high volume of applications..." that's application instructions boilerplate, remove.
Also "Applicants requiring employer sponsorship of a visa will not be considered for this position." That's also boilerplate? Might be considered a requirement but it's about visa sponsorship; it's a condition. Might be considered substantive? The instruction says remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The visa sponsorship line is likely part of application instructions, so remove.
Thus we keep only the substantive sections.
Now we need to format.
We'll have:
About the role
... (the paragraph about company and role)
Maybe also include purpose statement as part of About the role? Could be separate but we can include in same .
Better to keep as one paragraph.
Then
Responsibilities
- ... each responsibility as li
Then Requirements
maybe combine Required Technical Skills, Skills/Knowledge/Experience, Education... Could split into sub-sections but instruction says prefer few substantive sections over many thin ones. So we can combine all into Requirements section with lists.
We could have subheadings? Not allowed; only for section headings. So we can't have subheadings inside. We could just make one big list mixing all items. But we need to preserve all info; mixing is okay as long as we don't lose detail.
Alternatively we could have separate sections: Required Technical Skills, Skills/Knowledge/Experience, Education, Certifications & Designations. That would be more sections but each is substantive. The instruction says prefer a few substantive sections over many thin ones. Having four sections might be okay if each is substantive. But we could combine into Requirements.
I'll combine into Requirements with three sub-lists maybe using but we can't have headings inside. Could we use to label each group? Eg
Required Technical Skills:
then ... That's allowed because we can use for prose, and we can include bold text. That preserves info.
Thus:
Requirements
Required Technical Skills:
...
Skills / Knowledge / Experience:
...
Education, Certifications & Designations:
...
That seems fine.
Then Benefits
Insurance benefits:
...
Additional benefits:
...
We need to preserve all benefit items.
Now ensure we don't include any boilerplate like "We are proud to offer our employees, their domestic partners, and their children, a wide range of insurance benefits:" That's part of benefits intro; we can keep as .
Now check for any duplicated lines: I don't see duplicates.
Now produce HTML fragment.
Let's craft.
First, About the role paragraph: combine the initial paragraphs plus purpose statement maybe.
Paragraph: "We are looking for an FCAS to join the American Modern Predictive Analytics team as a Principal Data Scientist and play a key leadership role in advancing pricing model strategy. American Modern Insurance Group, Inc., a Munich Re company, is a widely recognized specialty insurance leader that delivers products and services for residential property – such as manufactured homes and specialty dwellings – and the recreational market, including boats, personal watercraft, classic cars, and more. We provide specialty product solutions that cover what the competition often can’t. We write admitted products in all 50 states and have a premium volume of $2.2 billion. Headquartered in Amelia, Ohio, and with associates located across the United States, we are part of Munich Re’s Global Specialty Insurance division. Our
- for any list of duties/requirements/benefits. Use
for prose. We must preserve all substantive info, not invent or summarize away detail. Must not include boilerplate like EEO, equal opportunity, scam warning, etc. Also remove duplicated lines. We need to be careful to keep all substantive details. Let's extract substantive content. First paragraph: "We are looking for an FCAS to join the American Modern Predictive Analytics team as a Principal Data Scientist and play a key leadership role in advancing pricing model strategy. American Modern Insurance Group, Inc., a Munich Re company, is a widely recognized specialty insurance leader that delivers products and services for residential property – such as manufactured homes and specialty dwellings – and the recreational market, including boats, personal watercraft, classic cars, and more. We provide specialty product solutions that cover what the competition often can’t. We write admitted products in all 50 states and have a premium volume of $2.2 billion. Headquartered in Amelia, Ohio, and with associates located across the United States, we are part of Munich Re’s Global Specialty Insurance division. Our employees receive boundless opportunity to grow their careers and make a difference every day - all in a flexible environment that helps them succeed both at work and at home." That's about the role/company. Next: "As a senior technical leader, you will drive the end-to-end development, enhancement, maintenance, and monitoring of personal lines pricing models. This role is highly visible and influential. While it does not include direct people management, it requires strong technical modeling skills, ownership of regulatory filings and objections, and mentorship of junior data scientists and analysts. As you grow in this role, the opportunity will extend beyond pricing, enabling you to contribute to broader predictive and decision science initiatives that support long-term enterprise purpose." Actually there is "Purpose: Use data and statistical analysis to drive business decisions and target improved results across various functional areas." That's a purpose statement. Then "Roles & Responsibilities:" followed by many sentences each maybe separate bullet. Let's list them: - Lead pricing model strategy for a subset of products. - Develop, deploy, monitor, and maintain predictive models. - Effectively collaborate with stakeholders. - Manage filing schedules for aligned products. - Prepare and complete predictive analytics analysis and modeling with guidance on very complex projects. - Participate in the development of predictive analytics and modeling presentations and present results/topics to customers (internal & external) and management as requested. - Concentrate on loosely defined problems which require application of creative approaches. - Contribute to projects that yield actionable insights the business can use to increase customer satisfaction, policy growth, retention, and profitability. - Complete required data preparation, including data input with guidance. - Identify data anomalies and seek guidance on necessary adjustments. - Identify data and operational issues requiring specialized analytics attention, data scrubbing, and modeling techniques. - Document and communicate assumptions, results, and alternatives to team members and internal customers with guidance. - Communicate with regulators when called upon to support rate filings or modeling practices in general. - Create and maintain modeling best practices and new techniques in coordination with internal and external business partners. - Explain advanced analytic and modeling procedures in the language that audiences with no predictive analytics training can easily find connections to. - Understand customers' requests and hidden issues and explain possible solutions in their language. - Schedule and prioritize workload demands. - Maintain very good organization skills. - Complete technical peer reviews as needed. - Maintain strong interpersonal skills - listen deeply, ask correct questions, take notes, complete professional oral and written business communications (including email communications), presentations, and build business relationships in order to better understand insurance company processes and functions. - Established relationships with multiple areas of interaction. - Mentor junior data scientists and team members. That's a lot. Then "Required Technical Skills:" list: - FCAS required. - Experience in multiple programming languages, including R and Python. - Deep understanding of GLMs and GBMs. - Familiarity with AI and machine learning concepts, including supervised and unsupervised learning, deep learning, and natural language processing. - Experience with Databricks or similar big data platforms is highly desirable. - Strong understanding of data structures, algorithms, and software design patterns. - Experience working in an agile team environment, with familiarity with Scrum or Kanban methodologies. - Strong commitment to testing, validation, and continuous improvement of models and workflows. - Proven experience with project management and prioritization. Then "Skills / Knowledge / Experience:" list: - Independently build models and statistical analyses. - Effectively communicate results to business partners and help drive business decisions. - Participate in creation and discussion of best practices and propose new techniques. - Manage projects and direct work of more junior team members. - Six (6) or more years of data science/predictive analytics experience in insurance or eight (8+) or more years predictive modeling experience in another industry. Then "Education, Certifications & Designations:" list: - Master’s degree in Business Analytics, Statistics, Computer Science, or Statistics/Math and Economics double major, or Statistics/Math and Computer Science double major or Statistics/Math and Operation Research double major. Then benefits: "We are proud to offer our employees, their domestic partners, and their children, a wide range of insurance benefits:" then list: - Two options for your health insurance plan (PPO or High Deductible) - Supplemental Life and AD&D plans that you can purchase for yourself and dependents (includes spouse/domestic partner and children) - Voluntary Benefit plans that supplement your health and life insurance plans (Accident, Critical Illness and Hospital Indemnity) - Prescription drug coverage (included in your health insurance plan) - Short and Long Term Disability coverage - Vision and dental insurance plans Then "In addition to the above insurance offerings, our employees also enjoy:" list: - A robust 401k plan with up to a 5% employer match - A retirement savings plan that is 100% company funded - Paid time off that begins with 24 days each year, with more days added when you celebrate milestone service anniversaries - Eligibility to receive a yearly bonus as a Munich Re employee - A variety of health and wellness programs provided at no cost - A hybrid environment that gives you a choice in where and how you get work done - A corporately subsidized on-site cafeteria as well as a We Proudly Serve coffee shop - An on-site complimentary workout facility as well as walking trails on campus grounds - On-site wellness center complete with nurse practitioner - Financial assistance for adoptions and infertility treatment - Paid time off for eligible family care needs - Tuition assistance and educational achievement bonuses - Free parking - A corporate matching gifts program that further enhances your charitable donation - Paid time off to volunteer in your community Then after that there is Diversity and Inclusion statement, EEO, etc which we should remove as boilerplate. Also there is "Sometimes we are fortunate enough to receive a high volume of applications..." that's application instructions boilerplate, remove. Also "Applicants requiring employer sponsorship of a visa will not be considered for this position." That's also boilerplate? Might be considered a requirement but it's about visa sponsorship; it's a condition. Might be considered substantive? The instruction says remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The visa sponsorship line is likely part of application instructions, so remove. Thus we keep only the substantive sections. Now we need to format. We'll have:
About the role
... (the paragraph about company and role)
Maybe also include purpose statement as part of About the role? Could be separate but we can include in same. Better to keep as one paragraph. Then
Responsibilities
- ... each responsibility as li
Requirements
maybe combine Required Technical Skills, Skills/Knowledge/Experience, Education... Could split into sub-sections but instruction says prefer few substantive sections over many thin ones. So we can combine all into Requirements section with lists. We could have subheadings? Not allowed; onlyfor section headings. So we can't have subheadings inside. We could just make one big list mixing all items. But we need to preserve all info; mixing is okay as long as we don't lose detail. Alternatively we could have separate sections: Required Technical Skills, Skills/Knowledge/Experience, Education, Certifications & Designations. That would be more sections but each is substantive. The instruction says prefer a few substantive sections over many thin ones. Having four sections might be okay if each is substantive. But we could combine into Requirements. I'll combine into Requirements with three sub-lists maybe using
- but we can't have headings inside. Could we use
to label each group? Eg
Required Technical Skills:
then- ... That's allowed because we can use
for prose, and we can include bold text. That preserves info. Thus:
Requirements
Required Technical Skills:
- ...
Skills / Knowledge / Experience:
- ...
Education, Certifications & Designations:
- ...
Benefits
Insurance benefits:
- ...
Additional benefits:
- ...
. Now check for any duplicated lines: I don't see duplicates. Now produce HTML fragment. Let's craft. First, About the role paragraph: combine the initial paragraphs plus purpose statement maybe. Paragraph: "We are looking for an FCAS to join the American Modern Predictive Analytics team as a Principal Data Scientist and play a key leadership role in advancing pricing model strategy. American Modern Insurance Group, Inc., a Munich Re company, is a widely recognized specialty insurance leader that delivers products and services for residential property – such as manufactured homes and specialty dwellings – and the recreational market, including boats, personal watercraft, classic cars, and more. We provide specialty product solutions that cover what the competition often can’t. We write admitted products in all 50 states and have a premium volume of $2.2 billion. Headquartered in Amelia, Ohio, and with associates located across the United States, we are part of Munich Re’s Global Specialty Insurance division. Our