About the Role
A data scientist will develop machine learning, data
mining, statistical and graph-based algorithms to analyze and make sense of
datasets; prototype or consider several algorithms and decide upon final model
based on suitable performance metrics; build models or develop experiments to
generate data when training or example datasets are unavailable; generate
reports and visualizations that summarize datasets and provide data-driven
insights to customers; partner with subject matter experts to translate manual
data analysis into automated analytics; implement prototype algorithms within
production frameworks for integration into analyst workflows.
Key Responsibilities
- Produce
data visualizations that provide insight into dataset structure and
meaning
- Work
with subject matters experts (SMEs) to identify important information in
raw data and develop scripts that extract this information from a variety
of data formats (e.g., SQL tables,structured metadata, network logs)
- Incorporate
SME input into feature vectors suitable for analytic development and
testing
- Translate
customer qualitative analysis process and goals into quantitative
formulations that are coded into software prototypes
- Develop
and implement statistical, machine learning, and heuristic techniques to
create descriptive, predictive, and prescriptive analytics
- Develop
statistical tests to make data-driven recommendations and decisions
- Develop
experiments to collect data or models to simulate data when required data
is unavailable
- Develop
feature vectors for input into machine learning algorithms
- Identify
the most appropriate algorithm for a given dataset and tune input and
model parameters
- Evaluate
and validate the performance of analytics using standard techniques and
metrics(e.g. cross validation, ROC curves, confusion matrices)
- Oversee
the development of individual analytic efforts and guide team in analytic
development process
- Guide
analytic development toward solutions that can scale to large datasets
- Partner
with software engineers and cloud developers to develop production
analytics
- Develop
and train machine learning systems based on statistical analysis of data
characteristics to support mission automation
Requirements
Qualifications
This position requires in-scope poly, within 7 years.
Bachelor's degree from an accredited college or
university in a quantitative discipline (e.g.,statistics, mathematics,
operations research, engineering or computer science). Five (5) years of
experience analyzing datasets and developing analytics, five (5) years of
experience programming with data analysis software such as R, Python, SAS, or
MATLAB. An additional four (4) years of experience in software development,
cloud development, analyzing datasets,or developing descriptive, predictive,
and prescriptive analytics can be substituted for aBachelor's degree. A PhD
from an accredited college or university in a quantitative discipline can be
substituted for four (4) years of experience.
- Programming
Languages: Proficiency in programming languages such as Python and R is
crucial for data manipulation, analysis, and implementing algorithms.
Python is favored for its simplicity and extensive libraries (likeNumPy
and pandas), while R is preferred for statistical analysis and data
visualization.
- Statistical
Analysis: A strong foundation in statistics and probability is necessary
for analyzing data accurately and making informed decisions. Understanding
concepts like regression analysis, hypothesis testing, and statistical
distributions is essential.
- Machine
Learning: Knowledge of machine learning algorithms and frameworks (such as
TensorFlow and Scikit-Learn) is vital for building predictive models and
automating decision-making processes.
- Data
Wrangling: The ability to clean and organize complex datasets is critical.
Data wrangling involves transforming raw data into a usable format, which
is often time-consuming but necessary for effective analysis.
- Database
Management: Familiarity with SQL and database management systems (like
PostgreSQL and MongoDB) is essential for extracting and manipulating
data stored in relational databases.
- Data
Visualization: Skills in data visualization tools (such as Tableau and
Matplotlib) help communicate findings effectively. Creating charts,
graphs, and dashboards is crucial for making data understandable to
stakeholders.
Salary Range 200-215,000
salary range provided is a general guideline. ISSI considers
several factors when determining compensation, including the role’s
responsibilities, candidate experience, education, skills, and current market
conditions.
Benefits
What We Offer
ISSI provides a highly competitive benefits package,
including:
- 401(k)
with matching contributions
- Health,
Dental, and Vision coverage
- Prescription
drug plans
- Employer-funded
Health Savings Account (HSA)
- Mental
health resources
- Life
and AD&D insurance
- Short-Term
and Long-Term Disability coverage
- Business
travel and expense reimbursement
- Employee
referral program with cash bonuses
- Employee
recognition program
- Tuition
and training reimbursement
Who Is ISSI?
ISSI is a growing management and technology consulting firm
specializing in systems and software solutions. Our team is dedicated to
delivering exceptional results for both our clients and employees.
Since our inception, we have focused on developing
innovative solutions that help organizations achieve their goals. We pride
ourselves on collaboration, technical excellence, and staying at the forefront
of emerging technologies.
Equal Opportunity Employer
ISSI is proud to be an Equal Opportunity Employer. All
employment decisions—including hiring, promotion, discipline, and
termination—are based on merit and business needs. We do not discriminate on
the basis of race, color, religion, age, genetic information, or any other
protected status under federal, state, or local law.