NannyML

NannyML is an Open Source Python library to detect silent model failure, estimate the performance of ML model even without ground truth, and robustly identify data drift.

Co-Founder and CEO

Prophecy Labs

Founder

Data Solutions. Elegantly Crafted.

Prophecy Labs helps companies automate complex work, optimize business processes, and predict events that impact your business.

Let our passion, be your edge.

Managing Partner

Essent.be

Developing a data platform in Scala/Spark to deal with large scale data and
deploying large scale machine learning models.

Big Data Engineer

SCK-CEN

This project was to help prepare for long term space travel namely a long term lunar outpost within the following decade. It involved working with gene expression data to help determine the effects of long term isolation and harsh condition on the human immune system. Data from workers of the Concordia platform in antarctica was used. Technical details of the R code can be found at the link below.

Research Bioinformatician 

Building an open source library to estimate the performance of deployed machine learning models in the absence of ground truth.

I love talking about: machine learning, decision making, post deployment data science, performance estimation, and bunch of other stuff. 

currently learning about: causal inference 

Always open to have a chat 🙂

Leave me anonymous feedback -> https://www.admonymous.co/hakim_elakhrass

🥸Hakim Elakhrass

building Soda to monitor the worlds data and decisions

Doctoral Researcher (CS) at University of Helsinki

Last week at the NeurIPS 2025 presenting our paper "Estimating Model Performance Under Covariate Shift Without Labels", which is joint work with Jakub Białek, Wojtek Kuberski, and Nikolaos Perrakis. What a highlight reel of talks, presentations and discussions! For those who can't wait until the proceedings are published, check out the paper in arXiv at https://lnkd.in/dME4FhMT.

Simplective

Data driven mentoring (consulting, Ai solution, training)

Chief data mentor (training ,consulting, ai solution architecture) 

As the pivotal bridge between clients and Data Science experts, I am responsible for:

Understanding Client Needs: I actively listen to clients to grasp their requirements and contextualize data within the broader business framework, ensuring a deep understanding of the core issues and their true motivations.
Problem Diagnosis and Solutions: I excel in diagnosing complex problems and formulating compelling, data-driven recommendations. My approach uncovers new business opportunities by leveraging insightful data analysis.
Strategic Planning: I assist companies and startups in developing a strategic approach that considers the big picture. This includes implementing data in formats that are best suited to project specifications.
Data Collection and Analysis: I determine the most effective methods for collecting, analyzing, and presenting data, ensuring compliance with all regulatory guidelines.
Experiment Tracking and Model Monitoring: I manage the planning and implementation of experiment tracking and model monitoring systems, facilitating collaboration among data scientists, IT professionals, and other stakeholders to ensure that models perform optimally and are integrated smoothly into business processes.
Leading and Managing Teams: I lead complex, interdisciplinary teams, guiding them through challenging projects and ensuring that every member is aligned with the project's goals and fully engaged in their roles.
Through these roles, I ensure that every piece of data is compliant and strategically aligned with our client's long-term goals, paving the way for informed decision-making and enhanced business performance.

 Consulting, Mentoring, and Training Services, Optimization of complex projects

Stat-Market Ltd.

Extensive experience building decision support systems (DSS) in education, healthcare, insurance, and fintech.


   Applied  Data Science Manager specializing in leveraging data to transform organizations into data-driven entities, excel in developing data-driven products, and leading teams to execute complex projects effectively.

Key Contributions:

Decision Support Systems: Enhanced insurance claims processing and retail recommendations using LTV models and psychological profiling.
Risk Management: Developed and implemented credit scoring and fraud detection models, significantly reducing risk exposure.
Predictive Analytics: Created models for churn prediction, anomaly detection, and cash forecasting, improving strategic decision-making and operational efficiency.
Economic Modeling: Spearheaded pricing sensitivity analysis and LTV prediction to optimize marketing strategies and financial management

Financial chief data scientist and AI project manager

Ernst & Young

The core of our method is to develop models of real-world problems that are easy to use, yet sufficiently realistic to support robust decision making
Our Expertise and Unique Approach:
Customer Analytics - Optimal pricing based on customer value, 
Using insight gained from analytics to develop customer retention/acquisition strategy and improve debt management.
Uplift Modeling -  empowers your organization to capture more than 100% of responses by contacting less than 100% of the target population

HR ANALYTICS - Predictive-Analytics-HR :
 Employee Profiling and Segmentation  
 Employee Attrition and Loyalty Analysis 
 Forecasting of HR Capacity and Recruitment Needs

Manager

MIA Computers/SAS Israel

Diversified activity with major focus in field of Credit Analytics, Business & Risk Intelligence,
Develop and implement risk methodologies, implement economic capital methodology, Scenario Stress Testing,Pricing strategies for retail products, develop portfolio management strategies on the increasing, decreasing, usage, extension and pricing of credit facilities to maximize profit,
Develop optimization strategies using advanced analytical SAS tools.

- יועצת בכירה ומנהלת פרויקטים, מיה מחשבים

G-STAT

-	Planning of CRM and email campaigns
-	Cooperation with analytic department 
-	Constant search of new opportunities for attracting our target users 

-	Provide statistical modelling, consulting and program development on Marketing and Credit Risk Models.
-	Cross-sell / up-sell modelling, customer segmentation, share of wallet modelling
-	Triggers and events based marketing, Next Best Offer recommendation modelling
-	Customer profitability forecasting, customer's current value and LTV modelling, sales prediction and development of supportive mechanisms for setting a sales quota, customer attrition prediction modelling, churn analysis, loyalty models, ROI models and market campaign optimization
-	Basel II and Credit Risk Modelling Consultant, expertise in the fields of: Merton models, improved Altman models, augmentation techniques for PD and LGD calculations, etc.
-	Validation of internally developed credit risk Probability of Default (PD), Loss Given Default (LGD) and Exposure at Default (EAD) models.

Data science mentor and team leader

Team Manager & Advanced Analytics leader:

--Leadership and Strategy: Directed the Data Department, managing both the model building unit and campaign management teams. Successfully led the development and execution of CRM and email marketing campaigns.
----Predictive Modeling and Analytics: Developed and validated predictive models for marketing optimization, HR analytics, and credit risk. Utilized advanced statistical and data mining methods such as Regression, Cluster Analysis, Basket Analysis, Decision Trees, and Neural Networks to enhance decision-making processes.
---Data-Driven Insights: Conducted in-depth research and analysis of products, customers, and market dynamics. Presented findings and strategic recommendations to senior management, significantly contributing to revenue growth and profitability.
----Technical Proficiency: Performed complex multivariable statistical analysis and forecasting using SQL on large databases including Oracle and Teradata. Developed statistical models that leveraged the bank’s marketing databases to optimize business outcomes.T

Project Management Team Lead

Bank of Israel

-	Responsibilities included statistical programming in support of economic research, software development using various statistical and econometric software packages and maintaining and updating databases
-	Executed advanced statistical analysis using modern statistical modelling techniques
-	Participated in the seminars and discussions held by the Research Department

Statistician

Hebrew University of Jerusalem

Research Assistant in joint project of School of Economics and Social Work

Research Assistant

At the forefront of fintech innovation, my expertise in AI and strategic planning has consistently driven transformative results. Over 13 years as a Chief Data Scientist and AI Project Manager, I've developed decision support systems that have revolutionized insurance claims processing and financial risk management. Our team's predictive analytics capabilities have enabled us to significantly reduce risk exposure for the organization.

With a blend of technical acumen and leadership, I've fostered collaborative environments where data-driven decisions are the norm. My approach to mentoring in data science not only uncovers business opportunities but also empowers teams to execute complex projects with precision. My role has been pivotal in aligning data science with business goals, ensuring that every solution we implement maximizes its potential to enhance our company's strategic direction.

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