Daniel Jin Email & Phone Number

At Datascension, we offer a transformative, story-driven curriculum that bridges the gap between traditional boot camps and graduate programs. Spanning a broad range of high-quality topics, our program focuses on career readiness and mastery rather than rushing learners through in 3-6 months. Whether you're a beginner exploring data or a professional advancing your career, Datascension provides the tools, projects, and support to help you succeed.Our unique approach integrates education with storytelling, making learning engaging and fun. Through interactive quests and challenges inspired by relationship and dating themes, you'll solve problems for a diverse cast of characters while mastering foundational concepts. This story-driven experience immerses you in real-world scenarios, combining entertainment with education to enhance understanding and retention.As you progress, you’ll move into the project phase, completing complex, real-world challenges tailored to your chosen pathway. From designing dashboards to building tools and performing in-depth data analyses, you’ll develop a portfolio of industry-relevant skills. For example, Analytics Engineers work on data architecture, dbt, Python, SQL, GCP, Tableau, and Dagster, showcasing strategic and technical expertise.What sets Datascension apart is our focus on helping you tell your story to employers. Beyond gaining skills and completing projects, we equip you to communicate your value through tailored resume and ATS optimization, storytelling strategies, and mock interviews. Our results phase ensures you’re prepared to enter the job market with confidence and impact.By combining storytelling, practical skill-building, and rigorous career preparation, Datascension transforms learners into strategic, proactive problem-solvers. Our program is designed to make learning purposeful, enjoyable, and effective, empowering you to excel in data-driven roles and confidently navigate your career journey.

Chicago, Il, Us

via Jobot (3 month contract)Engineered an automated data exploration tool in Snowflake using Python and SQL, enhancing data discovery processes and reduced the exploratory data analysis (EDA) process to 1% of what was needed without the tool.Designed and implemented a Snowflake-based data architecture to unify HR, sales, and inventory data from Workday, CRM (Salesforce and Hubspot), and ERP systems into a single source of truth (SSOT), significantly improving data consistency, enhancing leadership confidence, and aligning decision-making across departments.Built an automated ELT pipeline with Python, dbt, and Airflow, establishing a single source of truth that reduced manual intervention by 90% through automated ingestion, validation, and integration, enabling consistent, real-time cross-departmental analysis.Architected a galaxy schema with fact and dimension tables in Snowflake, connecting employee performance, sales, and inventory data to enable multidimensional analysis and cross-departmental reporting for more holistic insights.Developed a semantic layer and Tableau dashboards with real-time KPIs, offering insights into how employee performance and inventory levels influence sales outcomes, increasing strategic responsiveness, and enabling optimized workforce and inventory planning during peak demand.Implemented a data governance framework with automated auditing, data lineage, and a dynamic data dictionary, ensuring transparency and reliability across all data models.Served as tech lead in redesigning and building data models within the new architecture, guiding best practices and alignment with project goals.

Pasadena, California, Us

Championed Spokeo’s inaugural data quality assurance initiative, establishing KPIs and creating a Tableau dashboard that enhanced real-time data accuracy for Sales, Engineering, and Product teams, resulting in improved customer reconnection efforts.Developed a Python-based tool for automated SQL data quality checks, enabling non-technical teams to independently verify data accuracy and reducing query times by 100%.Migrated legacy ETL pipelines to a dbt-driven ELT architecture, improving execution time by 40% and cutting operational costs by 20%, while resolving data quality issues through dbt’s unit testing framework.Architected a unified data model in Redshift, integrating data from Workday, Greenhouse, and culture events to create a single source of truth for HR metrics, enabling real-time insights and faster decision-making in employee engagement and retention.Built a self-service analytics platform, providing HR teams with real-time insights that reduced decision-making time by 30%, fostering greater independence from analytics functions.Developed a predictive attrition model to identify high-potential and at-risk employees, decreasing attrition rates by 12% and enhancing succession planning efforts.Collaborated with GTM teams to implement a data-driven lead scoring model, resulting in a 15% increase in conversions and a 40% reduction in time spent on unqualified leads.Partnered with the product team to implement A/B testing strategies for new product features, improving feature adoption rates by 18% and delivering key insights that guided product roadmap decisions.Led cross-departmental data literacy workshops, accelerating the adoption of self-service analytics tools.Managed two direct reports, emphasizing a proactive approach to problem-solving by guiding them to focus on business challenges rather than task completion, fostering ownership and innovation in achieving objectives.

New York, New York, Us

Developed an automated claims approval system with Python, dbt, SQL, and GCP, reducing claim processing time by 95% and easing claim advisors’ workload, which contributed to a 10% YoY sales increase as client adoption grew.Implemented employee engagement analytics tools, including pulse surveys and NLP-driven Slack analysis, which identified early disengagement signals and improved overall employee engagement by 12%, reducing turnover through targeted interventions.Innovated custom Python scripts to automate client onboarding in dbt, SQL, and Dagster, dynamically generating schemas and SQL models, which reduced data onboarding time by 40% and model development time by 33%.Designed and built dashboards in Looker for long-term disability and schema mapping checks in BigQuery, automating data quality checks and anomaly detection, reducing validation time from hours to minutes, and enhancing consistency in onboarding processes.Created internal tools, including a data table comparison tool to assess the impact of code changes on data pipelines and a one-click dbt model creation tool, improving operational efficiency and developer satisfaction through streamlined automation and CI/CD practices.Developed a feature extraction tool for unstructured notes, enhancing machine learning model performance by 10% across client projects through improved data completeness.Mentored junior analysts and engineers by promoting best practices in data analysis and advanced tools, enhancing their problem-solving capabilities and technical execution.

San Antonio, Tx, Us

Trained and mentored the next generation of data professionals, equipping students with practical, industry-relevant skills in SQL, Tableau, and Python to excel in real-world data analytics roles.Led comprehensive modules in SQL, Tableau, and Python, guiding students through hands-on projects that simulated real business challenges, ensuring they gained practical experience in data manipulation, visualization, and analysis.Developed and delivered tailored curriculum that broke down complex concepts into accessible lessons, ensuring a diverse range of learners— from beginners to advanced— could successfully grasp key analytics tools and techniques.Provided personalized feedback and support, helping students to troubleshoot code, optimize SQL queries, and design compelling Tableau dashboards that clearly communicated data-driven insights.Fostered a collaborative learning environment, encouraging peer-to-peer learning, discussions, and group problem-solving to enhance students' critical thinking and analytical abilities.Created capstone projects that allowed students to showcase their skills in real-world data scenarios, preparing them for success in data analyst, data engineer, and data scientist roles upon program completion.Engaged in continuous curriculum improvement, incorporating the latest industry trends and tools to ensure students were job-ready and competitive in the rapidly evolving field of data analytics.

Seattle, Washington, Us

Developed a Dockerized Jupyter Notebook extension with an automated OAuth2 flow and user-friendly Python utilities, streamlining API adoption and reducing setup time by 50%. This enhancement doubled API usage, boosted potential revenue by 25%, and increased customer satisfaction by 50%.Architected end-to-end data solutions for multiple clients using various source systems, including SAP, NetSuite, Salesforce, HubSpot, Amplitude, and Segment. Integrated automated pipelines with Koverse's data platform to create a central data repository, improving data accessibility and decision-making efficiency across client operations.Consulted with business partners to gather requirements and implement tailored data analysis solutions, presenting insights that identified new growth opportunities and competitive advantages.Automated reporting of key KPIs and insights using Python, resulting in a 90% reduction in time to insight compared to the previous exploratory dashboard, which accelerated decision-making for stakeholders.Developed and optimized data pipelines in PySpark, ensuring efficient processing of millions of records and seamless integration into Power BI dashboards for enhanced data visualization and reporting.Utilized Sigma to create interactive dashboards and reports, enabling clients to access and visualize their data in real-time, which improved engagement and facilitated data-driven decision-making.

Washington, Dc, Us

via NetImpact Strategies Developed an Entity Resolution Application that identified high-risk entities, leading to a 33% reduction in operational costs and significantly enhancing FinCEN's effectiveness in detecting money laundering activities through improved data accuracy and insight generation.Built scalable ETL workflows with PySpark and SQL to process and cleanse large financial datasets, reducing data duplication by 33% and improving accuracy for high-priority investigations.Executed comprehensive data cleaning, profiling, and ETL processes using SQL, Python, and PySpark, ensuring data integrity and reliability while facilitating informed decision-making.Designed and implemented real-time data quality checks, enabling faster insights and reducing overall data processing times by 40%, which enhanced responsiveness to emerging threats.Automated data profiling and validation processes, streamlining the data validation process across key operational datasets and improving data quality checks.Led the development of scalable data architecture, optimizing workflows for terabyte-scale datasets, reducing execution times by 40%, and enhancing overall operational efficiency.Collaborated with cross-functional teams to deliver actionable insights in bi-weekly reports, translating complex data into clear strategies that informed senior leadership’s decision-making.Incorporated storytelling techniques in presentations to communicate actionable insights, showcasing strong communication skills and a data-driven approach to problem-solving.Developed predictive models and workforce forecasting tools, improving HR planning capabilities and optimizing staffing allocation for enhanced operational efficiency.

Falls Church, Virginia, Us

via ReefPoint Group and JDSATAutomated reporting processes for Navy Medicine, reducing manual reporting time by 20% and delivering critical insights for operational readiness and strategic decision-making.Developed Python scripts to integrate disparate data sources, enabling real-time data synchronization across medical databases and improving data accuracy by 15%.Built interactive HR analytics dashboards in R Shiny and Tableau to provide real-time visibility into manpower and engagement metrics, supporting informed workforce management decisions.Designed automated data validation scripts, improving data integrity across departments by catching errors early in the process, reducing manual intervention, and enhancing data accuracy.Created classification models for medical readiness and conducted predictive analysis to assess waiver request acceptance probabilities, improving resource planning.Streamlined reporting workflows by automating monthly, weekly, and daily reports using Python, reducing manual effort by 50% and ensuring timely decisions regarding medical readiness.Led the automation of people analytics reporting, cutting reporting time by 90% and improving data accuracy using Python and SQL, providing actionable workforce insights to leadership.Developed Python scripts to generate PDF, Excel, and PowerPoint reports, reducing manual effort by 100% and ensuring timely and consistent report delivery across leadership teams.Collaborated with stakeholders to gather precise business requirements, delivering ad-hoc reports and analysis swiftly and ensuring business needs were met on tight deadlines.Created self-service exploratory data analysis tools using R Shiny and Tableau, empowering stakeholders to uncover valuable insights independently.Identified process optimization opportunities and created innovative solutions using Python, improving efficiency across reporting, data management, and analysis workflows.

Columbus, Ohio, Us

Paris, Île-De-France, Fr

Master Of Science - Ms, Business Analytics

Bachelor Of Science - Bs, Mathematics

Micromasters, Analytics: Essential Tools And Methods

Micromasters In Data Science

Data Science Career Track

Data Analyst Nano Degree