Data Solutions Developer / Data Scientist IIFashion Institute of Design & Merchandising • Washington, Utah, United States
Data Solutions Developer / Data Scientist II
Fashion Institute of Design & Merchandising
- Washington, Utah, United States
- Washington, Utah, United States
About
Key Responsibilities Data & Analytics
Analyze complex datasets to identify patterns, trends, and opportunities that improve business decisions.
Develop data products including reports, dashboards, and visualizations to communicate business insights and KPIs.
Perform data acquisition, cleaning, transformation, and exploratory data analysis (EDA).
Engineer features and transform raw data into structured attributes for machine learning models.
Build and maintain advanced predictive models (classification, regression, time series, neural networks, NLP, computer vision).
Manage the end-to-end model lifecycle: development, deployment, monitoring, drift detection, retraining, and inference.
Tune models and conduct rigorous validation, testing, and quality evaluation.
Apply predictive models to enhance operational and business outcomes.
Automation, Low-Code Development & Process Optimization
Leverage Microsoft Power Platform (Power Apps, Power Automate, Power BI, etc.) to build business applications, automate workflows, and improve operational efficiency.
Optimize business processes by mapping current (“as-is”) and future (“to-be”) workflows and reengineering processes aligned to organizational goals.
Conduct root-cause analysis to identify process inefficiencies and propose technology-driven remedies.
Align automation strategies with project objectives and implement scalable automation solutions.
Collaborate on UI/UX design considerations to ensure applications and dashboards are intuitive and user-friendly.
Develop technical documentation, including SDLC artifacts, workflow diagrams, user guides, and requirements specifications.
Participate in unit testing, Quality Assurance (QA), and Quality Control (QC) activities to ensure solution reliability.
Contribute to system, software, or platform implementation efforts by supporting development, testing, rollout, and user adoption.
Work with IT, Infrastructure Technology, and Operational Technology teams to align analytics and automation capabilities with enterprise systems.
Build dashboards and business intelligence solutions that track project health, KPIs, and performance metrics.
Use collaboration tools (SharePoint, Teams, PowerApps) to support project communication, knowledge management, and version control.
Engage with customers and stakeholders to gather business requirements and deliver a strong customer experience.
Location Position is based on-site at a client office in Alexandria, VA.
Primary Location : United States - District of Columbia - Washington DC
Industry : Transit
Schedule : Full-time
Employee Status : Regular
Preferred Qualifications
Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Information Technology, or a related field
A minimum of 5 years experience strongly preferred
WMATA experience preferred
Preference given to candidates currently located in the area
Required Qualifications
A degree in a closely related field or combination of education and relevant experience
A minimum of 3 years experience with data engineering tools and languages such as SQL, Power Query, and Pandas
A minimum of 3 years experience with business intelligence tools such as Power BI, Tableau, Plotly, Seaborn, and Matplotlib
A minimum of 3 years experience with data science languages such as Python and R
Self‑motivated, detail‑oriented professional, ability to multitask a must
Proficiency with MS Office including Word and Outlook
Ability to handle confidential information
Excellent writing and people skills
Strong math and organizational skills
Flexibility and ability to prioritize and handle multiple tasks and various managers in a fast‑paced environment
Excellent verbal and written communication skills including grammar, punctuation, proofreading, spelling and telephone skills
An attitude and commitment to being an active participant of our employee‑owned culture is a must
In‑depth knowledge of machine learning algorithms, statistical models, and data analytics
Experience completing multiple data science projects
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Languages
- English
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