Harnham
Data Scientist - Insurance Analytics
Remote (10 am-6 pm EST)
6-Month Contract to Hire
$60-80/hr
About the Role
Our client, a specialized provider in the
non-standard insurance
space, is seeking a highly analytical and hands-on
Data Scientist
for a
6-month contract-to-hire
position. This role is ideal for someone with
3-5 years of experience
in data science or actuarial analytics, particularly within
insurance domains . The successful candidate will have a strong foundation in
predictive modeling ,
machine learning , and
insurance business applications
such as
loss modeling, retention analysis, and close rate modeling .
Key Responsibilities
Build and maintain
predictive models
focused on
loss prediction, retention, and close rates . Leverage
machine learning
techniques, including
time series analysis
and
unsupervised learning,
to uncover patterns in complex insurance data. Perform
data wrangling
to clean, merge, and transform datasets from multiple internal and external sources. Conduct
inferential statistical analysis
to support underwriting, pricing, and business strategy decisions. Collaborate with actuarial, underwriting, and business teams to translate data insights into actionable recommendations. Monitor model performance over time and support ongoing
model validation
and recalibration efforts. Develop compelling
data visualizations
and dashboards (preferably in Power BI; Tableau experience also acceptable). Communicate findings through strong
data storytelling and synthesis , tailored to both technical and business audiences. Required Skills & Experience
3-5 years of experience as a
Data Scientist , preferably within
insurance, actuarial analytics, or related domains . Strong programming and data skills: Python ,
SQL , and
R Proven experience with
data wrangling
and
ETL workflows Expertise in
predictive modeling
and
machine learning , particularly for
insurance applications Solid foundation in
inferential statistics ,
unsupervised learning , and
time series modeling Experience working with insurance data, including claims, underwriting, policy, and exposure data Strong experience in
data visualization
using
Power BI
or
Tableau Ability to present technical results clearly and persuasively to business stakeholders Nice to Have
Experience in
non-standard auto
or specialty insurance lines Progress toward actuarial exams (SOA or CAS) Familiarity with
cloud data environments
(e.g., AWS, Azure)
Remote (10 am-6 pm EST)
6-Month Contract to Hire
$60-80/hr
About the Role
Our client, a specialized provider in the
non-standard insurance
space, is seeking a highly analytical and hands-on
Data Scientist
for a
6-month contract-to-hire
position. This role is ideal for someone with
3-5 years of experience
in data science or actuarial analytics, particularly within
insurance domains . The successful candidate will have a strong foundation in
predictive modeling ,
machine learning , and
insurance business applications
such as
loss modeling, retention analysis, and close rate modeling .
Key Responsibilities
Build and maintain
predictive models
focused on
loss prediction, retention, and close rates . Leverage
machine learning
techniques, including
time series analysis
and
unsupervised learning,
to uncover patterns in complex insurance data. Perform
data wrangling
to clean, merge, and transform datasets from multiple internal and external sources. Conduct
inferential statistical analysis
to support underwriting, pricing, and business strategy decisions. Collaborate with actuarial, underwriting, and business teams to translate data insights into actionable recommendations. Monitor model performance over time and support ongoing
model validation
and recalibration efforts. Develop compelling
data visualizations
and dashboards (preferably in Power BI; Tableau experience also acceptable). Communicate findings through strong
data storytelling and synthesis , tailored to both technical and business audiences. Required Skills & Experience
3-5 years of experience as a
Data Scientist , preferably within
insurance, actuarial analytics, or related domains . Strong programming and data skills: Python ,
SQL , and
R Proven experience with
data wrangling
and
ETL workflows Expertise in
predictive modeling
and
machine learning , particularly for
insurance applications Solid foundation in
inferential statistics ,
unsupervised learning , and
time series modeling Experience working with insurance data, including claims, underwriting, policy, and exposure data Strong experience in
data visualization
using
Power BI
or
Tableau Ability to present technical results clearly and persuasively to business stakeholders Nice to Have
Experience in
non-standard auto
or specialty insurance lines Progress toward actuarial exams (SOA or CAS) Familiarity with
cloud data environments
(e.g., AWS, Azure)