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A Bit About Me

Hello there,

​

At the age of 15, I embarked on a journey that took me away from my home. I traveled extensively across Asia and the Middle East, engaging in a variety of customer service-focused roles. This journey eventually led me to establish a permanent residence in the United States, where I pursued a formal education in the fields of aerospace and petroleum engineering.

​

I've spent last 15 exciting years immersing myself in the world of transformation. From consulting to crafting machine learning software, I've been on a journey of discovery. One of my passions is untangling the web of information in multi-disciplinary teams to keep things flowing smoothly. Think of me as your go-to person for getting rid of those pesky bottlenecks.

I thrive on strategic systems thinking – connecting the dots to optimize processes and bring automation into play. But what really fuels my fire is putting the customer front and center. Their experience is what matters most to me.

​

Right now, I'm on the lookout for a leadership role that will let me spread my wings while expanding Sakura AI. My dream is to build cross-functional machine learning platforms that not only work like a charm but also elevate team collaboration. And let's not forget my knack for nurturing team growth and setting sights on the big picture.

So, if you're looking for a transformation leader who's not just about the tech, but also about the people and the impact, let's talk. I'm all ears and ready to bring my expertise to your table.

​

Best, Anna Nyulund

Work Experience

 2016 - Present

2022

2021 - 2022

2020

2018-2020

2018

2017 -2019

2017 -2019

2017 

2017 

2016 - 2017

2016 

2014 - 2015

2014 - 2015

2014 - 2015

2014 - 2015

Sakura AI

Founder 

Completing multiple turn-key machine learning contracts for various clients to establish cash flow for the platform development.

Apple 

Sr. Technical Project Manager (Contract)

  • Established short-term, middle-term,and long-term vision for a CapEx Manufacturing platform, connecting Environmental, Manufacturing, Financial, Marketing, and Hiring departments, tracking vendors and materials, managing resources ethically and environmentally, and predicting correct kick-off dates.

  • Set up reporting processes, team organization, and communications for cross-functional efforts and recruitment.

  • Developed and programmed front-end and back-end designs for software automation of CapEx Manufacturing Systems for

    iPhone, iPad, and MacBook Pro.

  • Set the standards for code, systems mapping, data mapping, and transformation.

Charter Communications

Data Science and Strategic Analytics Manager

  • Implemented agile project management processes and organized a diverse team of Data Scientists to develop a Chat Platform that decreased customer service live agent phone costs.

  • Proposed and implemented several strategies including departmental reorganization, NLP research lab formation, technical re- source optimization, and advanced neural net utilization.

  • Proposed hiring and retaining strategies, debiasing algorithm strategies, and data optimization and search strategies

  • Led the creation of Team API for software hand-offs and quality checks, templates for rapid analytics, research strategies, and

    documentation and code repository organization.

  • Achieved 20% increase in operational efficiency.

Northrop Grumman

Principal Data Scientist 

  • Interfaced with C-suite (engineering management and centers of excellence) to understand their requirements and effectively communicated them to the Data Science team.

  • Led the data science team in project development to meet C-suite requirements.

  • Created yearly projections for project development and determined necessary hiring needs.

  • Elevated the Data Science team to the next level, transitioning from self-serving BI Tools and Predictive Models to Autonomous

  • Human-Machine Interaction.

  • Developed and documented a Computer Vision model from scratch, including Data Engineering Pipelines, Data Processing,

  • Model Building, and Production enablement on local Linux-based workstations and in the cloud using AWS Sagemaker and Kedro Pipelines.

  • Interfaced with C-suite (engineering management and centers of excellence) to understand their requirements and effectively communicated them to the Data Science team.

  • Led the data science team in project development to meet C-suite requirements.

  • Created yearly projections for project development and determined necessary hiring needs.

  • Elevated the Data Science team to the next level, transitioning from self-serving BI Tools and Predictive Models to Autonomous

  • Human-Machine Interaction.

  • Developed and documented a Computer Vision model from scratch, including Data Engineering Pipelines, Data Processing,

  • Model Building, and Production enablement on local Linux-based workstations and in the cloud using AWS Sagemaker and Kedro Pipelines.

Oleum Scientia

AI Consultant

  • Collaborated closely with stakeholders, datascience, engineering, and QA teams to facilitate an efficient, collaborative, and high- quality product development process.

  • Conducted meetings with various clients to interpret their vision and strategy, establish a roadmap, and prioritize features based on the fastest time-to-market and highest impact.

  • Defined key performance indicators(KPIs) and metrics to measure the success of team-built features.

  • Attained an expert-level understanding of each client’s data to deliver solutions that increase user management and optimize business processes.

  • Proactively identified potential issues, integration points, and requirements beyond basic product needs.

  • Designed and integrated machine learning models on top of reservoir simulation software.

  • Developed algorithms for parsing Oil and Gas leases and deeds and implemented profile optimization analytics strategies resulting in cost savings and profits exceeding 100 million dollars.

  • Created and deployed machine learning models on top of real-time drilling operations using AWS SageMaker.

RigUp

Sr. Data Analyst

  • Developed a Deep Averaging Network to analyze polarity in contractor reviews.

  • Debiased word embeddings using cosine similarity functions in Scikit-learn library

  • Replaced GloVe with debiased word embeddings.

  • Integrated semantic analysis with the ranking algorithm as the base algorithm for the recommendation engine, resulting in a

  • profit of at least one million dollars in the first year of operation.

  • Transferred the company’s data warehouse to AWS with in two months, leading to smoother and faster running algorithms.

  • Mapped the entire data base with ERDs.

  • Built a custom NamedEntityRecognition(NER) engine using Python Spacy package for resume parsing.

  • Conducted interviews and hired junior analysts and machine learning engineers for the Data Science team.

DataJudo

Sr. Data Scientist

  • Royal Dutch Shell Oil Company:

    • Successfully completed optimization of a Petroleum Producing Assets Portfolio: Advanced Computer Model Development
      (Python) resulting in profit of over 300 million dollars over 5 years.

    • ​Simulated distribution of reserves and a set of expected production profiles using Monte-Carlo Analysis.

  • Chevron Corporation:

    • Developed petroleum price forecasts based on Sequential Gaussian Simulation.

    • Calculated after-tax cash flows, estimated performance indicators for each realization, thus yielding Distribution of return for each project.

    • Estimated covariance between return distributions of individual projects and compiled them into portfolios.

Merk

Sr. Data Scientist

  • Developed a model that predicted risk of non adherence for Januvia patient cohort resulting in savings of billions of dollars

  • Collaborated with a team of engineers and put in production a webcrawler that found fraudulent pharmacy websites and alerted the C-Suite to take legal action. Model development was completed in AWS.

Sensoleak

Sr. Data Scientist

  • Advised the CEO on setting up operations in the USA and building a local Data Science team, helped to select potential hires, conducted the interviews, and mentored junior Data Scientists and Engineers

  • Managed the workload, scheduled the assignments and deadlines based on the expertise of the teammembers, and conducted interdisciplinary business meetings between the clients and the team members

  • Developed a time-series pipeline detection model

USAA

Data Architect

  • Developed a behavior-based ML model to identify fraud and FICO accuracy testing algorithm using Kolmogorov-Smirnov statistics, Area Under the Curve, Receiver Operating Characteristic, and Population Stability Index.

  • Built Convolutional Neural Network prototype, which predicted the number of transactions based on the customer’s qualifications.

  • Improved Exploratory Data Analysis by implementing the Apriori Algorithm to find Association Rules in customer behavior.

Parsley Energy 

Spotfire Engineer

  • Developed Data Analytics Life cycle and Project Request Process for Spotfire

  •  Provided support for the development of production and reservoir data bases for Investments

  •  Used time series modeling to develop decline curve analysis and to setup a system of alerts to identify problematic wells

  •  Developed a pump failure prediction model which resulted in savings of over 100 million dollars

  • Developed Arps Curves code for production forecasting

  •  Developed Tableau and Spotfire dashboards for Lease Operating Expenses. The automation saved over 10,000 hours.

  •  Developed advanced code and automated dashboard for the Business Intelligence department

Devon Energy 

Data Scientist

  • Guided Integrated Reservoir Characterisation team in decision-making process for acquisitions and divestment (multi-million dollar decisions)

  • Developed ML learning algorithm which determined intermittent sedimentation. The algorithm resulted in savings of over 1000s of hours.

  • Developed prediction model for corrosion in completions casing which prevented well abandonment. Each well cost ranges from 5 to 15 million dollars. The company had over 300 wells.

  • Developed dashboards for Drilling, Production, Geology, Environmental Health, and Protection and communicated all insights to C-Suite on a monthly basis.

Schlumberger Information Systems

Data Scientist/ Reservoir Engineer

  • Developed a complex reservoir simulation analytics solution using advanced mathematical models and is being used today by different companies including Pattern Computer.

  • Coupled reservoir simulator with computer science algorithms (Multi-Armed Bandit and Colony Optimization Algorithms)

  • The solution development helped facilitate a sale of the Schlumberger oilwell services in the amount across the country. The development of one well is 1 million dollars.

  • The development resulted in a large academic accomplishment

Schlumberger Information Systems

Data Scientist/ Reservoir Engineer

  • Developed a complex reservoir simulation analytics solution using advanced mathematical models and is being used today by different companies including Pattern Computer.

  • Coupled reservoir simulator with computer science algorithms (Multi-Armed Bandit and Colony Optimization Algorithms)

  • The solution development helped facilitate a sale of the Schlumberger oilwell services in the amount across the country. The development of one well is 1 million dollars.

  • The development resulted in a large academic accomplishment

Gulf Interstate Engineering

GIS Analyst/ Mechanical Engineer

  • Developed a complex analytical model to identify pressure flow in a pipeline for the client (Pacific Oil and Gas)

  • Mapped the pipeline using GIS technology

  • The solution was a part of new government regulations and resulted in savings of hundreds of millions of dollars and hundreds of human lives

Halliburton

Directional Driller

  • Was in charge of over 40 staff on a drilling rig. Guided the team to conduct safe drilling operations.

  • Was the first female Directional Driller at Halliburton.

  • Developed projections to the well and interacted daily with clients (operating companies).

Education

  • Post Graduate Program, AI and Machine Learning, University of Texas at Austin, 2021

  • Post Graduate Program: Reinforcement Learning Specialization - the University of Alberta 

  • MS, Petroleum Engineering, University of Alaska Fairbanks, 2015

  • BS, Aerospace Engineering, the University of Texas at Austin, 2010

Certifications/ Training/ Classes

  • Machine Learning Model Deployment 2020

  • Machine Learning Pipelines in Spark 2020

  • Spark NLP 2020

  • RESTful APIs 2020

  • AWS Developer 2020

  • Computer VisionI, II, III; OpenCV, 2019-2020

  • Natural Language Processing (post-graduate work), University of Texas at Austin, 2018

  • Data Structures, University of Washington, 2019

  • SAS: DataScience Learning Path, 2016

Technical Skills

  • Programming Languages: Python, SQL, PySpark, Matlab, R (used in college) , C++(used in college)

  • Natural Language Processing: Semantic Analysis (DAN, LSTMs, encoder-decodermodels, RNN, BERT, Albert, Roberta, Flair, parsing of unstructured and semi-structured data (NER (custom CRF and Spacy), Regex, Topic Modeling (Gensim)) in PyTorch and TensorFlow and more (ask if you are curious)

  • Computer Vision: Open CV, Tesseract (OCR)

  • Data Processing: NLTK, Spacy, OpenCV, SKLearn, Pandas, Numpy, SQL

  • Data Visualization: Tableau, Spotfire, SAS VA, Seaborn, Matplotlib, Bokeh, Plotly

  • Data Engineering/ Cloud: AWS (EC2, Lambda, ElasticBeanstalk, SageMaker) , Google Cloud, Azure, SQL, PostgreSQL, ERD construction, Flask, RESTful API, Docker, Postman

  • Machine Learning: Datacleaning, parsing and processing, DeepLearning, Supervised and Unsupervised Methods, NLP and Computer Vision, and more (ask if you are curious)

  • Big Data: Hive, Hadoop HDFS, Kafka (KSQL)

  • Agile Project Management: Jira, Target Process, Azure DevOps

  • Data Science Project Management: SEMMA, KDD, CRISP-DM, Agile

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