AIQ is the leading Industrial AI solution provider in the MENA region with a $1.4B valuation.

I am leading the development of an ML-based optimization solution for oil and gas production - RoboWell. The solution is deployed across 5 oil and gas fields with over 500 well counts.

𝗔𝗰𝗵𝗶𝗲𝘃𝗲𝗺𝗲𝗻𝘁𝘀:
✅ Identified 3 ML/MLOps sub-products and improved DS task delivery time by 20% by developing 
a roadmap, prioritizing tasks, and optimizing resource allocation for the solution scale-up phase. 
The sub-products include ML Models Monitoring Report, ML Proxy Model, and Data Quality Control.

✅ Saved $3M/year by developing end-to-end ML Proxy Modeling and Monitoring Pipelines that eliminated the cost of sub-contractors and reduced software license costs used for proxy model generation.

✅ Improved by 22% the ML solution MAPE error by designing model validation, data cleaning, and hyperparameter tuning strategies and supervising their implementation by the team.

Principal Data Scientist

Conundrum

Conundrum is an Industrial AI company that develops a SaaS platform for optimal control of metals and mining assets.

𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀:
🟢 Led a team of 7 data scientists in the development of machine learning modeling and optimization solutions.
🟢 Covered client communication, team management, problem formulation, model development, and solution deployment of complex ML / optimization solutions.
🟢 Data Science team hiring, growth, and development.
🟢 Support of the sales and business development from the AI-product strategy and pre-sale perspectives.

𝗔𝗰𝗵𝗶𝗲𝘃𝗲𝗺𝗲𝗻𝘁𝘀:
✅  Increased by $60M+ customer revenue by delivering 4 real-time end-to-end ML solutions that optimized ore processing and smelting plants. The solutions showed 2.5%+ increase of plants throughput and stabilized by 25%+ of the product variability.

✅  Identified potential $50M customer revenue improvement by completing 5 bottleneck analysis projects for Tier-1 metals and mining companies, resulting in new projects with them.

✅ Grew and structured a DS team from 5 to 20 data scientists who formed 4 internal teams responsible for specific solution directions.

✅ Supported closing of 3 multi-million contracts by providing technical support to the sales and business development teams.

✅ Reduced by 400%+ the time of development and deployment of ML applications by creating a machine learning pipeline template based on Kedro framework.

✅ Decreased from 15 to 3 days the data quality assessment time by creating a standard library that generated consistent data quality reports for new client data.

✅  Improved by 70% the DS team task completion rate within a sprint by introducing and adapting Scrum practices.

𝗨𝘀𝗲𝗱 𝘁𝗼𝗼𝗹𝘀 𝗮𝗻𝗱 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀:
Git | GitLab | Kedro | Great Expectations | MLFlow | Scikit-Learn | XGBoost | CatBoost | PyTorch | Keras | Numpy | Pandas | SHAP | Plotly | Matpotlib | Seaborn | Scipy

Ctrl2GO Global

Ctrl2Go is one of the major AI solution providers for the railway and energy industries in the RCIS region.

𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀:
🟢 Led a team of 5 data scientists in the development of predictive monitoring machine learning models for various industrial equipment. 
🟢 Structured and optimized the company's business to enhance the efficiency of the data science team's contributions.

𝗔𝗰𝗵𝗶𝗲𝘃𝗲𝗺𝗲𝗻𝘁𝘀:
✅  Increased by 2.3% smelting plant production by supervising the solution development for optimal ore blending using MINLP formulation in Pyomo.

✅ Created a comprehensive model database/library for quicker deployment of the existing solutions in new projects.

✅ Formulated product development directions to the C-level management of the company based on the existing clients and partners and the data science team's expertise. It allowed the company management to prioritize development directions, understand risks, and estimate costs.

𝗨𝘀𝗲𝗱 𝘁𝗼𝗼𝗹𝘀 𝗮𝗻𝗱 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀:
Git | GitLab | Kedro | Great Expectations | MLFlow | Scikit-Learn | XGBoost | CatBoost | PyTorch | Keras | Numpy | Pandas | SHAP | Plotly | Matpotlib | Seaborn | Scipy | Pyomo

Head of Data Science

Zyfra Company

Zyfra is one of the major Industrial AI solution providers in the RCIS region.

𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀:
🟢 Led a team of 3 data scientists in the development of ML solutions for problems in the petroleum industry including process modeling, optimization, and anomaly detection.
🟢 Covered Industrial AI-based product strategy formulation, management, development, and sales.

𝗔𝗰𝗵𝗶𝗲𝘃𝗲𝗺𝗲𝗻𝘁𝘀:
✅ Increased by 1.2% oil and gas production for 2 clients by leading the from-scratch development of the 
”AI Oil Optimization Assistant” solution. This is web-based ML software for accurate prediction and optimization of oil and gas production in real-time by using machine learning and advanced dynamic optimization algorithms.

✅ Increased by 5% the drilling speed and reduced by 50% the stuck pipe occurrence on a pilot test by developing a real-time ML solution to detect drilling pipe sticking events.

𝗨𝘀𝗲𝗱 𝘁𝗼𝗼𝗹𝘀 𝗮𝗻𝗱 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀:
Git | GitLab | Kedro | Great Expectations | MLFlow | Scikit-Learn | XGBoost | CatBoost | PyTorch | Keras | Numpy | Pandas | SHAP | Plotly | Matpotlib | Seaborn | Scipy | Casadi

Senior Data Scientist

Norwegian University of Science and Technology (NTNU)

I was developing advanced industrial ML approaches for combining machine learning with process engineering physics for multiphase flow and reservoir modeling and equipment degradation monitoring.

𝗔𝗰𝗵𝗶𝗲𝘃𝗲𝗺𝗲𝗻𝘁𝘀:
✅ Reached TOP 6 most cited papers in Computers and Chemicals Engineering Journal (Q1) within
the last 3 years based on the Scopus citation system.
✅ Reached TOP 3 in the ranking of most downloaded papers for 2 publications in 2 Q1 journals.
✅ Reached over 300 citations within 3 years of active publishing.

𝗨𝘀𝗲𝗱 𝘁𝗼𝗼𝗹𝘀 𝗮𝗻𝗱 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀:
Scikit-Learn | XGBoost | PyTorch | Keras | Numpy | Pandas | Plotly | Matpotlib | Seaborn | Linear Regression | Bayesian Neural Networks | Feed-Forward NN | Gradient Boosting | Random Forest

Researcher in Industrial Machine Learning

PSRE Co (NTP Truboprovod)

✅ Developed a model to predict severe slugging occurrence in pipeline networks and stability map representation.
✅ Developed a model to calculate transport of solids (flow regime and pressure drop) in single and multiphase steady-state flows for different flow patterns.
✅ Adopted industrial standards to calculate erosion rate in pipelines with single and multiphase flows.
✅ Developed a model of reciprocating compressors for equipment selection and performance evaluation purposes.

Multiphase Flow Models Developer

HOERBIGER

✅ Developed a calculation spreadsheet for the estimation of an oil production increase by wellhead compression technology.
✅ In a team of 2 application and 5 service engineers, completed 6 projects on supplying reciprocating compressor parts according to the customers’ needs.
✅ Assisted my colleague in a project of reciprocating compressor upgrade and revamp by developing a 3D compressor model in SolidWorks software.

Application Engineer

✅ Developed a dynamic model of a reciprocating compressor for CO2  compression in Modelica.

Visiting Researcher

Principal Data Scientist with over 8 years of experience in the full lifecycle of Machine Learning solutions, including strategy development, value discovery, code implementation, deployment, and monitoring. 

My expertise in ML and Optimization enables the creation of robust, accurate solutions, driving $3-10M in additional annual revenue per project.

As a Data Science Manager, I have 4 years of experience in leading, hiring, and managing data science teams. I am capable of organizing team work under harsh deadlines and complex project scopes. 

𝐈 𝐚𝐥𝐬𝐨 𝐞𝐧𝐣𝐨𝐲 𝐡𝐞𝐥𝐩𝐢𝐧𝐠 𝐨𝐭𝐡𝐞𝐫 𝐃𝐚𝐭𝐚 𝐏𝐫𝐨𝐟𝐞𝐬𝐬𝐢𝐨𝐧𝐚𝐥𝐬 𝐠𝐫𝐨𝐰 𝐢𝐧 𝐭𝐡𝐞𝐢𝐫 𝐜𝐚𝐫𝐞𝐞𝐫 𝐛𝐲:
- Upgrading their CVs/LinkedIn
- Providing 1:1 Career Mentoring
- Sharing Free Practical ML Materials to support their technical growth

𝐌𝐲 𝐚𝐜𝐡𝐢𝐞𝐯𝐞𝐦𝐞𝐧𝐭𝐬 𝐨𝐯𝐞𝐫 𝐭𝐡𝐞 𝐩𝐚𝐬𝐭 𝐬𝐞𝐯𝐞𝐫𝐚𝐥 𝐲𝐞𝐚𝐫𝐬:

✅ Increased by $60M+ customer revenue by delivering 4 real-time end-to-end ML solutions that optimized Metals and Mining assets. During the projects, successfully managing the team of 7 Data Scientists. The solutions showed 2.5%+ increase of plants throughput and stabilized by 25%+ of the product variability.

✅ Identified potential $50M customer revenue improvement by completing 5 bottleneck analysis projects for Tier-1 metals and mining companies, resulting in new projects with them.

✅ Increased by 1.2% oil and gas production for 2 clients by leading the from-scratch development of the "AI Oil Optimization Assistant" solution. This is an ML software for accurate prediction and optimization of oil and gas production in real-time by using advanced ML and Optimization algorithms.

✅ Grew and structured a DS team from 5 to 20 data scientists who formed 4 internal teams responsible for specific solution directions.

► Tech Skills: Machine Learning | Data Science | AI | Data Analytics | Predictive Analytics | MLOps | Time Series | Anomaly Detection | Deployment  | Optimization | Git | Kedro | MLFlow | Scikit-Learn | XGBoost | Numpy | Pandas | SHAP |  Scipy | Docker

► Soft Skills: Team Management | Leadership | Empathy | Project Management | Presentation Skills | Problem Solving | Stakeholder Management

Timur Bikmukhametov, PhD

Alex Molinar

Geological Technician/Jr Geologist

Dallas Digital Data

•	Developed two working proof of concepts for AI applications, showcasing potential transformative impacts on business operations through advanced analytics.
•	Successfully trained and tested custom ChatGPT and LLaMA2, LLaMA3 models, enhancing conversational AI capabilities.
•	Built and deployed AI assistants, demonstrating proficiency in zero-shot learning and mastery in multimodal models.
•	Managed three use cases in the proof of concept phase, aimed at further integrating AI solutions into scalable business applications.
•	Utilized Vector Databases to enrich the knowledge base of AI assistants and implement local, Google-like search functionalities, optimizing data retrieval and user interaction.
•	Developed machine learning algorithms to reduce Non-Productive Time in drilling operations, saving up to $1 million per event.
•	Led the creation of an automated platform increasing geoscientific productivity by 500% through advanced data analysis.
•	Implemented robust data governance frameworks to ensure data integrity and compliance across all projects.
•	Robust list of small business clients available upon request.
• Along side a team, developed cutting-edge real-time drilling support models that harness real-time drilling data to detect wear on the drill bit. This inventive solution drastically reduced operational downtime, thus saving time and resources and boosting the overall efficiency of drilling operations.

• Conceived and executed an automated platform for the precise identification of horizontal productive
zones. This pioneering system dramatically freed up valuable geoscientist time, and simultaneously
improved the precision of mapping, resulting in an enhanced understanding of subsurface resources.

• Designed and implemented a Python web scraping application specifically tailored for a leading Real Estate Foreclosure company. This innovative tool skillfully gathers and consolidates data from three disparate sources into a streamlined SQLite database.

Senior Data Scientist Consultant

Hunt Oil Company

•	Spearheaded the Land Digitization Project using optical mark recognition technology to digitize and organize land files, enhancing document retrieval and information accessibility.

•	Developed real-time drilling support models using real-time drilling data to detect bit wear and rig state, reducing operational downtime.

•	Created an automated platform for horizontal productive zone identification, freeing up geoscientist time and improving mapping precision.

•	Automated the cleaning, preparation, and importing process of high-frequency data into Well Data Labs, increasing productivity of completion engineers.

•	Modernized an ArcGIS web tool that calculates well construction cost based on proximity to infrastructure, improving budget planning accuracy.

•	Led API integrations using Python and the SAP Integration Suite, enhancing data exchange and software functionality.

•	Conducted extensive training on programming and data science best practices, fostering a data-driven culture within the organization.

•	Developed a sophisticated simulation model for wind farm expansion and commercial battery integration, serving as a pivotal tool in strategic planning.

Primexx Energy Partners

•	Created field development optimization program on Primexx's largest asset. Used three different programming languages based on the best use case. Custom generated java program to visualize the field development, ArcGIS Pro with python for infrastructure design and modelling, and finally production modelling using Spotfire with R. I combined data from Operations, Geology, Land and Engineering departments into the application. CI/CD Standards were observed to speed up implementation. ROI: ETL software development with modeling all in house. Saved millions.

•	Business Intelligence (BI) visualization specialist using data from each department (land, legal, accounting, engineering and financial using) Spotfire, Tableau and Matplotlib depending on the requirements and funding of the department and the capabilities of each package. ROI: No outsourcing visualizations.

•	Generate and maintain databases that include data form state regulatory agencies, field meters, and private vendors (3rd party API). The database was designed to support unique software packages of each department. The database was automatically updated from multiple vendors sources. The purpose was to monitor our areas interests utilizing using multivariable logistic regression and to better analyze trends in the Permian Basin. ROI: Basin wide analysis with small team. Saved millions.

•	Create entire Data Science workflow including data mining and dashboard generation for VP of Petrophysics to calibrate masks of Nuclear Magnetic Resonance with core data in our primary asset. Incorporated principle component analysis and support vector machine to predict rock properties with limited core data. Saved over 6 months of time and several million dollars. ROI: Exceeded VP project estimates by six months two weeks into project.

•	Demonstrate the ability to learn new and create new processes, workflows, policies, and procedures. Supervise, train and lead geologists, petrophysicists, geophysicists, accountants, and others in python for data exploration, visualization, storage, and machine learning. ROI: No outsourcing training.

•	Provide support within busy office in all aspects of the exploration and production business. Prepare reports, spreadsheets and presentations for investor meetings; manage records; and administer Petra and SMT (Seismic Micro Tech) database. Review prospects and new projects and report to Exploration Manager ROI: Create reproducible workflows reducing the required number of employees. 
.
•	Generate a company wide database used to keep track of production and inventory. The database was used extensively by Primexx for many years for investor and regulatory reporting. Generated VBA scripts use to populate the database from excel datafiles. ROI: Company wide data base.

Data Scientist

Fagadau Energy Corporation

•	In 2001, spearheaded the rollout of Petra and Kingdom Software. Prior, Primexx was doing entire geologic evaluations by hand. Was tasked with generating projects and training Senior Geologists. 

•	With minimal training from Primexx’s senior geologist I was assigned to perform Well site geology for in West Texas for three years evaluating Spraberry, Strawn, Atoka and Mississippian samples and reporting to Exploration Manager and management team. Generate sample logs and analyze samples for several wells post drilling, and participated in mudlogging during key intervals to aid in the decision-making process for completions and identification of potential pay zones.

•	Was part of a team at Primexx that discovered and developed a 1280-acre field (20 MMBO) extension by stratigraphically detailing conventional Spraberry debris flow fan deposit in northern Borden county. Calculated reservoir volumetrics in pay sand intervals to extend a field and to assist in a Waterflood simulation.

Experienced Data Science senior professional. I am a highly motivated and positive individual, I thrive on embracing challenges and seeing the positive in everything. With proficiency in several programming languages and excellent time management skills, I am adept at handling complex tasks. Being a people person, I find joy in teaching and learning from others, and I firmly believe in the importance of mentorship for personal growth. Family is the cornerstone of my life, and I value the significance of looking people in the eye and being patient to foster understanding. My philosophy centers around embracing mistakes as opportunities for learning, viewing science as a continuous journey of growth. Let's work together to achieve greatness, empowering one another to be passionate about what we do and to see the big picture in all that we undertake.

Owner, Chief Data Scientist

• Along side a team, developed cutting-edge real-time drilling support models that harness real-time drilling data to detect wear on the drill bit. This inventive solution drastically reduced operational downtime, thus saving time and resources and boosting the overall efficiency of drilling operations.

• Conceived and executed an automated platform for the precise identification of horizontal productive
zones. This pioneering system dramatically freed up valuable geoscientist time, and simultaneously
improved the precision of mapping, resulting in an enhanced understanding of subsurface resources.

• Designed and implemented a Python web scraping application specifically tailored for a leading Real Estate Foreclosure company. This innovative tool skillfully gathers and consolidates data from three disparate sources into a streamlined SQLite database.

taplio

The Battle

Timur Bikmukhametov, PhD

Alexander Joel Molinar Sr

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