Über
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.
Sprachkenntnisse
- English
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