Dana Kaplan Email & Phone Number

San Francisco, Ca, Us

San Francisco, California, Us

Engineer working in large batch data ingestion and transformation efforts.● Tools Utilized: Airflow, Ascend, Snowflake, Python, Spark, AWS Ecosystem.● Created and owned ETL pipelines for terabyte-scale data deliveries utilizing Spark and Snowflake. Managed and reviewed contractor work on those pipelines.● Helped successfully design and launch a cheaper, faster, more flexible data ETL transition effort with “in house” tooling replacing SAAS components.● Adhered to rigorous standards for our canonical data layer and wrote automated QA tools to surface issues.● Led the development of our data lineage tools to help profile batches through our complex systems and delete, fix, or monitor them.

San Francisco, California, Us

Oakland, California, Us

Responsible for data infrastructure, ingestion, validation, reporting, tightly scheduled external extracts to banking partners, and began analytics and ML infrastructure.● Tools Utilized​: Python3, Spark, Docker, Airflow, Terraform, AWS Ecosystem (Redshift, S3, EC2, EMR, parameter store)● Helped design and develop our nightly batched data process overhaul to a faster, more centralized, and flexible Redshift based architecture.● Managed critical on-call support for external and internal issues for a data process with airflow debugging, triaging issues, descriptive logging, and flexibility within our ingestion and processing systems. ● Began ML infrastructure design and development process

San Francisco, California, Us

Responsible for automated data validation, processing, transforming, feature extraction, and QA for various sources of messy andunstructured scraped web data. ● Tools Utilized:​ Python3, Spark, Docker, Airflow, Postgres, AWS Ecosystem.● Worked closely with Data Scientists to support initiatives with useful and cleaned data sets built from Spark pipelines. ● Brainstormed additional potential value from our unstructured web scrapes and also helped impute and smooth rough data features with M.L.● January 2019 Company Hackathon Winner​: “Packaging Image Styles” - Working proof of concept utilizing a Pretrained Neural Net (VGG19) to build a latent distance metric between packaging image “styles” to help cluster, find similarities, or use as feature engineering.

San Francisco, California

Structured and modeled customer support conversations with NLP and clustering techniques. Identified common intents of conversations and helped build our model to classify intents and move the conversation into the most useful “flows”.● Tools Utilized:: Python (Pandas/Sklearn/Flask/Notebooks), TensorFlow, Gensim, AWS Ecosystem.

Boulder, Colorado, Us

Participant in an immersive and intensive data science program emphasizing both practical and theoretical machine learning, statistics, modeling, natural language processing, visualization, and modern technologies in distributed data.● Tools Utilized : : Python (Pandas/Matplotlib/Sklearn/Flask/Notebooks), AWS Ecosystem, Spark, MongoDB, SQL● Capstone Project: The Missing Piece - Boardgame recommender to assess your game collection and generate suggestions that both(1) you will enjoy and (2) satisfy preferences you don't have covered. Utilizes non-negative matrix factorization to generate feature topic clusters and makes recommendations from measuring topics a game collection is ‘weak’ in.

San Francisco, California, Us

One of the three founding members of the Data Science Team at Scribd. Responsibilities were focused on ETL, data warehousing and pipelines, analysis and modeling, and data communication.● Tools Utilized : : Hive/Impala/MySQL, Python, Ruby/Rails, Tableau.● Owner and architect of Tableau integration at Scribd.● Hive and SQL maintenance: cleaning, schema migrations, backfilling, bug fixing, optimizing run times, integrating new product datainto existing aggregates and tables, etc...● Analysis projects, such as understanding our Audiobooks launch and exploring "onboarding" test groups.● Integrated with Algorithmic Book Recommendation team (Tasks included exploring JS data logging errors, optimizing the nightlySQL aggregation and matching, to providing dashboards and analytics on KPIs).

General self managed, all-purpose data guy in a small start-up who works with engineering, marketing, sales, and client facing teams. Focused on time saving Python scripting, product improvement & client retention analytics, and operational methods & queries to implement Hive into all aspects of the company. A sample of tasks in no particular priority: scripted/automated client reporting, supplied data/wrote HiveQL for Accounts, Sales, and Marketing requests, improved our ad bidder through analytics, product managed our reports scheduler and client facing reporting interface, designing a client diagnostic tool to help accounts find advertising campaign performance improvement, helping set up quality control for our daily Hive ETL tasks, etc...Tools utilized: ● Hive/HiveQL ● Python ● Ruby/Rails/ERB ● Tableau ● Git/Github ● Pivotal Tracker ● Advanced Excel

Oakland, California, Us

Used Excel (VBA) & Tableau to interpret and utilize data for Blurb & Citrix Online clients. Gathered, cleaned, managed, and presented data in self designed dashboards and sophisticated worksheets. This included daily data maintenance for live campaigns, final analysis of KPI performance, and suggestions for future planning.Helped new employees in best Excel and data management practices.___Previously, I helped plan, buy, report, and analyze various Sega of America's online, search, and print campaigns.Sonic Pulse Dashboard: Designed and successfully pitched an ongoing analytics dashboard to measure the combined and individual effectiveness of Mediasmith’s and Sega’s “Sonic” various branding efforts. This project quantitatively measures elements that could impact brand buzz.

San Francisco, California, Us

Cleaned, organized/planned the databases, and analyzed various large aviation data sets using UNIX/AWK/MySQL/Python/Excel.Co-designed a tool to analyze profitable flight opportunities in weather emergencies using predictive elements of our data collection as well as a machine-learned neural network.

MTH235 - Linear Algebra in Fall 2008 ECO207 - Microeconomics in Spring 2009Graded assignments and exams; Led workshops and recitations. Answered student emails and met individually with them.

Becket, Ma, Us

Brought joy to the world; Responsible for 8 to 15 year old campers; 24 hours a day. Communicated progress with parents. Created and organized activities and games for both small and large groups. Taught daily sessions in drawing and arts & crafts.

Hoodie Of Academic Achievement, Machine Learning & Data Science

Bs, Ba, Mathematics (Bs), Economics (Ba)