Continuous Improvement Machine Learning
Resume:
Darius Bell
** ****** **, ******, **, United States, 27703 910-***-****
*************@*****.***
Portfolio
Results-oriented Data Scientist with 10+ years of overall data engineering and analytics experience, including 5+ years developing and deploying advanced machine learning models. Adept in Python (Pandas, NumPy, SciPy), data mining, and productionizing analytics solutions. Proficient in Azure ML and OpenAI services, with a proven track record of transforming complex data into actionable insights. Skilled at collaborating with cross-functional teams to solve business challenges, drive continuous improvement, and communicate findings in a clear and concise manner.
● Core Strengths: Advanced ML model development, Python coding, data processing, feature engineering, model deployment, stakeholder communication, data-driven decision making. Professional Experience
Owner
Bell Contracting Services LLC, Raleigh-Durham, NC
August 2024 - Present
● Founded a contracting firm specializing in government contracts, offering a full suite of services: deliveries, lawn care, power washing, trash pickup, and general maintenance.
● Oversee end-to-end operations, including business development, client relations, and quality control, ensuring all services meet rigorous government standards and deadlines.
● Partner closely with government agencies to provide reliable, cost-effective solutions that enable them to focus on core responsibilities.
● Lead a dedicated team committed to safety, professionalism, and continuous improvement, consistently delivering superior results that uphold the highest levels of quality and integrity. Manager
Merck, Raleigh-Durham, NC
April 2023 - August 2024
● Lead cross-functional teams in developing and deploying end-to-end data science solutions, including advanced ML models to optimize laboratory workflows and reduce operational bottlenecks.
● Oversee data collection and cleansing processes, ensuring the integrity and regulatory compliance (e.g., HIPAA, FDA) of structured and unstructured data.
● Leverage Python and Azure ML services to build, train, and deploy predictive models that drive real-time decision-making for sterility and microbiological data.
● Integrate OpenAI API prototypes to expedite data analysis and improve lab documentation management, collaborating with IT to define secure deployment strategies.
● Engage with stakeholders to present complex analytics outputs, providing actionable insights for continuous improvement in quality, productivity, and cost savings.
Key Achievements
● Designed and productionized a predictive analytics pipeline that decreased testing cycle time by 30%.
● Introduced advanced feature engineering methods, improving model accuracy by 20% across multiple validation studies. Senior Quality Specialist
Merck, Raleigh-Durham, NC
November 2019 - April 2023
● Developed machine learning models in Python (scikit-learn, Pandas) to identify and mitigate potential deviations in sterile product testing.
● Conducted data mining activities from multiple sources (SAP, TrackWise, GLIMS) to build comprehensive datasets for advanced analytics and forecasting.
● Collaborated with cross-functional teams to deploy analytics solutions in production, ensuring minimal downtime and robust monitoring of deployed models.
● Drove a culture of data-driven decision making, mentoring team members on statistical modeling, predictive analysis, and data visualization techniques.
Key Achievements
● Automated data extraction workflows, saving the team 20+ hours per week in manual report generation.
● Led ML-based anomaly detection initiative, reducing lab deviations by 15% within six months of deployment. Quality Specialist
Merck, Raleigh-Durham, NC
April 2018 - November 2019
● Utilized Python scripting to preprocess, cleanse, and validate large volumes of microbiology data for sterility, bioburden, and potency testing.
● Created dashboards and visualizations (Tableau, Power BI) to highlight data patterns, operational KPIs, and improvement areas.
● Collaborated with IT to enhance data collection procedures and ensure alignment with analytics system requirements.
● Spearheaded continuous improvement projects to streamline ETL pipelines, boosting efficiency and data accuracy for lab operations.
Key Achievements
● Delivered data-driven insights that led to a 25% reduction in sterility testing rework.
● Established robust data integrity protocols that became a model for other product lines within Merck. Senior Specialist (Merck Contractor)
Onboard, Raleigh-Durham, NC
October 2017 - April 2018
● Performed lab data management and testing using LIMS.
● Coordinated with cross-functional teams to ensure compliance with regulatory standards. Graduate Research Assistant
Tallahassee, FL
August 2014 - April 2017
● Built and analyzed predictive models using Python to assess environmental data sets, driving scientific insights into habitat health.
● Conducted data extraction and transformation processes to integrate multiple environmental data sources into unified datasets.
● Mentored undergraduate students in statistical analysis, experimental design, and data visualization techniques. Key Achievements
● Implemented machine learning workflows for fish health assessments, contributing to multiple peer-reviewed papers.
● Pioneered new data collection methods, enhancing overall data quality and reducing sample processing time by 15%. Education
Master’s Degree in Environmental Science
Florida Agricultural and Mechanical University
August 2014 - April 2017
Concentration in Biotechnology
Bachelor of Science in Biology
East Carolina University
August 2010 - July 2014
Interest
● Data Visualization: Exploring innovative ways to represent complex datasets through interactive dashboards.
● Emerging Technologies: Staying updated on advancements in AI, machine learning, and big data tools.
● Mentorship: Passionate about guiding junior analysts and fostering a collaborative team environment.
● Geospatial Analysis: Enthusiastic about leveraging GIS tools to integrate spatial data into actionable insights.
● Continuous Learning: Pursuing certifications and workshops to enhance data analytics expertise. Projects
Demand Forecasting Models
● Built predictive models leveraging Python (Scikit-learn) to improve forecasting accuracy by 20%. Route Optimization
● Developed and deployed machine learning models to optimize delivery routes, reducing transportation costs by 15%. Data Visualization and Reporting
● Designed dynamic dashboards in Tableau, improving stakeholder understanding of data trends.
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Certifications
IBM Data Science Specialization
Applied Data Science Capstone
Foundations of Cybersecurity
Skills
● Programming & ML Frameworks: Python (Pandas, NumPy, SciPy, scikit-learn), Azure ML, OpenAI APIs, PyTorch/TensorFlow (familiar)
● Data Engineering & Visualization: SQL, ETL pipelines, data cleansing, feature selection, data visualization (Tableau, Power BI)
● Cloud & Deployment: Azure (Data Factory, ML Studio), Docker, CI/CD pipelines, RESTful APIs
● Machine Learning Techniques: Regression, classification, clustering, optimization, deep learning fundamentals
● Project & Stakeholder Management: Agile methodologies, cross-functional collaboration, presenting technical findings to non-technical audiences
● Tools & Platforms: Git, JIRA, Confluence, SAP, TrackWise, KNEAT, GLIMS, Veeva Vault
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