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Devowise Studios

Web Design Studio | Brand Identity | Framer & AI Solutions

$5k+: Earned

4x: Hired

5.0: Rating

133: Followers

expert

Expert

+4

Web Design Studio | Brand Identity | Framer & AI Solutions

Cover image for Scalable Azure Data Engineering Solution Implementation

Scalable Azure Data Engineering Solution Implementation

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Cover image for Development of Studio Lumen's Yoga & Wellness Platform

Development of Studio Lumen's Yoga & Wellness Platform

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10

Cover image for Zynox AI Conversational Platform Development

Zynox AI Conversational Platform Development

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4

Cover image for Lets Have Pets | Full-Stack Mobile App Development

Lets Have Pets | Full-Stack Mobile App Development

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5

Aïn Bénian, Algeria

Data Scientist

5.0: Rating

4: Followers

Data Scientist

Cover image for Hi Contra , a big part of my work is building ML projects en...

Hi Contra , a big part of my work is building ML projects end to end, from exploration to deployment. I work across the full lifecycle: • 🔍 EDA & data validation on large, messy datasets • 🧩 Feature engineering with PySpark driven by business logic • 🧠 Model training & evaluation (time-series & ML) • 🚀 Production pipelines & deployment On the engineering side, I focus on making ML reliable and scalable: • PySpark pipelines for feature engineering, batch training & inference • MLflow for experiment tracking, model versioning & reproducibility I enjoy working with teams that care about clean ML systems, not just experiments , especially when models need to be trusted and reused. 👉 If you’re looking for someone to build ML pipelines end to end , from data exploration to production I’m open to contract or freelance work.

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Cover image for 👋 Hi Contra — I’m Lilya, a Data Scientist working at the in...

👋 Hi Contra — I’m Lilya, a Data Scientist working at the intersection of retail, demand forecasting, and promotion analytics. My recent work focuses on SKU-level forecasting, where small modeling choices have a big business impact: • 📦 Improving SKU-level demand forecasts for planning & inventory • 📊 Approximating the pull-forward effect of promotions On the technical side, I work end-to-end: • Time-series & ML forecasting • Promo, price & calendar feature engineering • PySpark batch pipelines & MLflow tracking 💡 Open to freelance or contract projects around demand planning, retail analytics. Happy to connect 🚀

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Cover image for 🧠 Hi Contra, alongside retail forecasting, I’ve worked on a...

🧠 Hi Contra, alongside retail forecasting, I’ve worked on applied NLP and computer vision projects that go beyond experiments and turn into real solutions. I’ve built: • Review rating prediction with BERT • Text summarization using FLAN-T5 • Sign language classification • Fruit disease detection with Fast R-CNN • A neural-network chess move predictor What I enjoy most is shaping messy data, choosing the right models, and evaluating solutions realistically. 👉 If you’re building NLP or computer vision products and need someone hands-on, I’d love to connect.

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Cover image for 🤖 Hi another side of my work is building LLM-powered system...

🤖 Hi another side of my work is building LLM-powered systems that actually ship. I’ve worked on chatbots and AI assistants from research to production, focusing on usefulness and reliability: • Designing LLM-based recommenders using LangChain & FAISS • Fine-tuning transformer models (BERT, T5 / FLAN-T5) for real NLP tasks • Testing, debugging, and improving chatbot behavior based on user feedback ⚙️ Tech I often use: PyTorch, Hugging Face, LangChain, vector search, MLflow 💡 Open to freelance or contract work where teams need: • LLM integration or fine-tuning • Chatbots or AI assistants that deliver real value • Practical NLP solutions, not demos Happy to connect with teams building AI-driven products 🚀

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216

Berlin, Germany

Product Analytics Consultant

New to Contra

Product Analytics Consultant

Cover image for Main analyst for the Supply

Main analyst for the Supply Loyalty program, maintaining engagement of our main supply source in the Rides Vertical. Interim Lead for the Supply Analytics team for 6 months, during which i’ve provided valuable guidance to my peers and regular 1-1s, clarifying ambiguous requirements, delegating functional tasks In my time as interim lead, i have also brought in Focus days as part of a 20% discovery time agreement. I have also introduced a review system for our work in order to increase the quality of our output End-to-end feature development, from recognising high stakes opportunities to delivering in-app experiences through data modelling. Cross functional collaboration, with stakeholders such as Group Product Managers, Engineering Managers and functional analytics leads Personal roadmap management guaranteeing on time delivery, completely autonomous Mentoring of other colleagues during organisational changes, such as highlighting opportunities that could benefit both org and individual contributors

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Cover image for * Started off as an

* Started off as an intern and grew to be a Data Scientist * Prepared ETLs for better ingestion of stream data * Worked cross functionally together with Product Managers and Engineers on delivering features, both for the B2C and B2B part of the business * Performance measuring of Computer Vision models by working closely with the Computer Vision team Set up internal emailing system that would automatically deliver reports and raw data inside the company for better performance - reducing waiting times for the Operations team and unblocking them to best achieve their goals

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Cover image for * Delivered on a number

* Delivered on a number of projects within the Service Product Line, projects including: * Rider Customer Chat * Customer Agent Chat * Fraud detection (Exploit) * Event Tracking system (internal solution for tracking) * First analyst within projects, set up from scratch all of the tracking, AB Testing and setting up an analytics mentality, North star metrics, monitoring and troubleshooting * Led cross functional discussions among Analysts, Engineers, Product managers and Operations analysts, which moved the needle further. * Brought in a more collaborative mentality among analysts, and set up weekly sharing sessions, as well as informal follow ups. This in the end created more trust, a happier team and better quality of deliverables for stakeholders.

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Cover image for * Main point of contact

* Main point of contact for Data Science aspects for Candy Crush Jelly Saga , third game of the Candy Crush Franchise * Delivered important features together with a cross-functional team (such as Player vs. Player, Ads, Buddies) instrumental to achieving strategic goals within the game and at an organisation wide level * Responsible of all AB Tests in the game: AB test design, open questions in pre-production, release monitoring, final feature analysis * Made impactful recommendations on how to improve the game, by aligning with key stakeholders on strategic goals * Advocate for mentoring and data transparency: held mentoring sessions with Junior colleagues as well as with the team on the tools they can use to independently make data driven decisions

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AI Engineer | Agentic Systems & Automation | MLOps

New to Contra

AI Engineer | Agentic Systems & Automation | MLOps

Cover image for I engineered a large-scale package-network

I engineered a large-scale package-network intelligence pipeline using Azure Databricks and PySpark. The system joined approximately 4.5 billion historical records and transformed them into reusable fingerprint signals covering package movement and network behavior. I developed time-windowed feature logic using native Spark expressions rather than Python UDFs, preserving distributed performance at scale. The pipeline produced an approximately 200-million-row fingerprint dataset and a 22-million-row operational output that classified package activity along a cold-to-hot temperature scale. The resulting signals supported downstream monitoring, prioritization, and operational analysis. The architecture shown here is a sanitized representation; client identifiers, proprietary schemas, infrastructure paths, and business rules have been removed.

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Cover image for Last week I shipped a

Last week I shipped a full learning platform: two audience journeys (students + tutors), subscriptions and digital-product sales, lead capture, blog — built solo, end to end.

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161

Cover image for I designed and engineered a

I designed and engineered a hierarchical multi-agent orchestration framework for coordinating complex AI-assisted engineering and analytical work. A central orchestrator assigns bounded tasks to specialized builder, analyst, reviewer, and verification agents. Execution follows an explicit dependency graph, while shared evidence, acceptance gates, negative-path testing, and checkpointed state prevent agents from declaring work complete without proof. The framework supports targeted retries, rollback, and recovery from the first incomplete node instead of restarting an entire workflow. It also separates implementation from independent review, reducing the risk of an agent validating its own unsupported conclusions. This independent engineering project demonstrates how agentic systems can be made more controlled, observable, and recoverable. The architecture and control interface are representative views of the framework rather than screenshots containing private execution data.

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Cover image for I developed an AI-assisted document-intelligence

I developed an AI-assisted document-intelligence workflow for transportation-agency teams working with large collections of reports, standards, studies, scanned documents, and project records. The system combined document extraction, OCR, structured metadata, semantic retrieval, knowledge relationships, and grounded LLM responses. Analysts could ask questions in natural language, review the supporting evidence, inspect source citations, and approve, revise, or reject generated findings. The workflow was designed around human review, access controls, traceability, and safe failure rather than treating an LLM response as an unquestionable answer. Related work reduced decision time by approximately 60% and improved data accuracy by approximately 35%. The displayed architecture and interface are sanitized representations and contain no client documents, production data, proprietary prompts, or confidential system details.

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153

Software Engineer | AWS | React | Databricks | Frontend

New to Contra

Software Engineer | AWS | React | Databricks | Frontend

Cover image for I designed and deployed an

I designed and deployed an end-to-end Enterprise Lakehouse on Azure Databricks for DineDash, a multi-city food delivery platform. The business was facing severe data fragmentation across disparate CSV dimensions and streaming JSON orders, along with data quality gaps that distorted revenue and driver metrics. To solve this, I built a production-grade Medallion Architecture combining Unity Catalog Volumes, Delta Live Tables (DLT) with real-time Data Quality firewalls, 27 SQL analytical models, an Executive BI Dashboard, and an Automated Databricks Workflow DAG that refreshes the entire platform seamlessly without manual intervention."

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Cover image for Linkedin-Auto
This project is made to

Linkedin-Auto This project is made to automate the data collecction process and the messeaging to the managers for a job or to increase some valuable connections

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Cover image for Refactor a Sudoku Game written

Refactor a Sudoku Game written in Python Flask Use this simple Sudoku game as a starting point to practice your skills with GitHub Copilot. The goal is to refactor the code to use modern technologies, while also adding new features and improving the overall user experience.

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Cover image for Aditya-Kumar

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Results-driven Data Engineer & Full-Stack Developer building

Results-driven Data Engineer & Full-Stack Developer building

Cover image for Real-time NFL Draft Prediction Model Deployment

Real-time NFL Draft Prediction Model Deployment

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Cover image for Real-Time Rental Market Analytics Application

Real-Time Rental Market Analytics Application

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Cover image for Real-Time Marketing Offer System

Real-Time Marketing Offer System

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6

Cover image for Portfolio

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Summerville, USA

Talented Data Engineer | Data Architecture

Talented Data Engineer | Data Architecture

Cover image for Databricks to Terraform Export Transformation

Databricks to Terraform Export Transformation

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10

Cover image for 301 Moved Permanently

301 Moved Permanently

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6

Cover image for Development of DataTrackPro Analytics Platform

Development of DataTrackPro Analytics Platform

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8

Cover image for Automic ETL Development for Lakehouse Architecture

Automic ETL Development for Lakehouse Architecture

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Rajkumar Chatterjee

Advisory Consultant: Leveraging Data for Better Decisions

Advisory Consultant: Leveraging Data for Better Decisions

Cover image for Provided independent architecture reviews and

Provided independent architecture reviews and second-opinion guidance for leadership teams evaluating complex data and platform decisions, helping surface risks early and validate strategic design choices.

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71

Cover image for Senior advisory engagement focused on

Senior advisory engagement focused on guiding data and platform strategy for a regulated enterprise, with emphasis on architectural direction and decision-making rather than delivery

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Cover image for Advisory engagement focused on guiding

Advisory engagement focused on guiding domain owners and architects on data product and domain-driven architecture principles, helping align data structure, ownership boundaries, and platform design for long-term scalability.

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Cover image for Fractional architecture leadership engagement supporting

Fractional architecture leadership engagement supporting solutioning and design decisions for a UK-based asset management firm, providing architectural direction, design reviews, and decision support without owning delivery execution.

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