Data Scientist & Engineer Needed

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Matlab, Python, and similar tools. I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@saba106

I am an expert statistician, Research Writer, and data analyst with more than eight years of experience. I have full command of Excel analysis, SPSS, STATA, R LANGUAGE, AND PYTHON. I am an expert in creating time series prediction models, working with survey data, conducting marketing analysis, building estimators, and medical analysis. I am a perfect match for your project share other details of the work so I can start working on your project. Will complete task on time.

@AhmadXpert2410

Hi there, I’m an experienced Data Scientist with a strong background in Python, SQL, and machine learning frameworks like TensorFlow, PyTorch, and Scikit-learn. I can help transform Gradlynk into an AI-driven platform by collecting, cleaning, and analyzing student data to generate actionable insights, build predictive models, and personalize learning experiences. My focus will be on enhancing student engagement, forecasting performance trends, and improving operational efficiency across your edtech ecosystem. I’ve worked extensively with data pipelines, cloud platforms (AWS/GCP/Azure), and visualization tools, translating complex analytics into clear, actionable recommendations for both technical and non-technical stakeholders. I can design models that are interpretable, reliable, and aligned with educational objectives while ensuring high data quality and consistency across systems. I can collaborate closely with your Product, IT, and Operations teams to integrate AI-driven features into Gradlynk, provide ongoing monitoring of model performance, and deliver dashboards or reports that make insights immediately usable. With a focus on actionable, data-backed improvements, I’m ready to help take Gradlynk to the next level. Regards,

@Shrutibimpl

Hello, I will design and implement an AI-driven analytics layer for Gradlynk by first consolidating and cleaning your student data using a robust SQL-based pipeline. I will then develop predictive models using popular ML frameworks to personalize the student journey and forecast performance trends. These models will be integrated into your existing CRM through secure APIs. I will also build interactive dashboards using standard visualization tools to provide clear, actionable recommendations for your stakeholders. My focus will be on ensuring high data quality and low-latency model inference, leveraging your preferred cloud platform to maintain a scalable edtech ecosystem. 1) What is the specific database engine used by Gradlynk ( PostgreSQL, MySQL)? 2) Which cloud platform is your current infrastructure hosted on (AWS, Azure, or GCP)? 3) Are there specific student performance metrics you want to prioritize for the initial forecasting model? Thanks, Bharat

@mayankinnovative

Transforming Gradlynk into an AI-driven CRM requires first establishing a reliable data foundation before layering predictive intelligence on top. I would begin by auditing existing data sources, schema consistency, and event tracking to ensure clean, well-labeled datasets suitable for modeling. Building structured pipelines for ingestion, validation, and feature engineering will prevent downstream bias and inaccuracies. Next, I would develop predictive models focused on engagement scoring, dropout risk forecasting, and personalized content recommendations using Python-based ML frameworks. Model outputs would be exposed through APIs or embedded analytics modules that integrate directly into Gradlynk’s workflows. Clear dashboards and interpretable metrics will translate model insights into actionable recommendations for educators and administrators. Continuous monitoring, A/B testing, and retraining cycles will ensure models evolve with user behavior. The objective is measurable impact: improved retention, optimized communication timing, and data-backed operational decisions across your edtech ecosystem.

@vishal1145

Your Gradlynk CRM is sitting on a goldmine of student interaction data, but without predictive models, you're reacting to churn instead of preventing it. If students are dropping off without early warning signals, you're losing revenue and missing intervention opportunities when they matter most. Before architecting the ML pipeline, I need clarity on two things: What's your current data volume - are we talking 10K or 500K student records? And does Gradlynk expose APIs for real-time feature extraction, or will we need to build ETL pipelines from scratch? Here's the technical approach: - PYTHON + SCIKIT-LEARN: Build student engagement scoring models using logistic regression and random forests to predict dropout risk 30 days in advance with 85%+ accuracy. - SQL + POSTGRESQL: Design star schema data warehouse with indexed fact tables to run cohort analysis queries in under 2 seconds, even at 1M+ records. - AWS SAGEMAKER + LAMBDA: Deploy serverless ML inference endpoints that score students in real-time as they interact with the platform, triggering automated intervention workflows. - TABLEAU/POWER BI: Create executive dashboards showing leading indicators - not just lagging metrics - so your team can act on trends before they become problems. - TENSORFLOW: Implement recommendation engine that personalizes learning paths based on historical performance patterns across similar student profiles. I've built 4 predictive systems for edtech clients that increased retention by 22-35% by identifying at-risk students early. I don't take on projects where the data infrastructure is unclear. Let's schedule a 20-minute call to review your current data architecture and define success metrics before committing to a build.

@WiredAI

Hi, This role is a great fit for what I do. I work hands-on as a Data Scientist helping teams turn existing CRMs and platforms into AI-driven systems that actually improve engagement and decision-making—not just dashboards. I can help you clean and structure Gradlynk’s data, build predictive and personalization models, and work closely with your product and IT teams to embed AI features directly into the platform. I’m comfortable with Python, SQL, ML frameworks, cloud-based pipelines, and translating complex findings into clear, practical insights for non-technical stakeholders. I’ve worked on data products where education outcomes, user behavior, and operational efficiency all mattered, and I focus on building models that are reliable, explainable, and useful in real workflows. Happy to discuss how we can make Gradlynk smarter and more impactful. Best, WiredAI Ventures

@Biplove1769

I'll transform Gradlynk CRM into an AI-driven edtech platform with data science & machine learning. Expertise: - Python (pandas, numpy, scikit-learn, TensorFlow) - SQL & database optimization - Statistical modeling & predictive analytics - ML frameworks (XGBoost, LightGBM) - Data visualization (Matplotlib, Plotly, Tableau) - AWS/Azure/GCP & data pipelines - Edtech/CRM experience Deliverables: ✓ Integrate & analyze Gradlynk data (CRM, student interactions, outcomes) ✓ Predictive models: engagement, learning outcomes, dropout risk ✓ Personalization engine: content recommendations, adaptive paths ✓ Operational optimization: resource allocation, enrollment forecasts ✓ AI feature integration with IT/Product/Operations teams ✓ API development for model deployment ✓ Real-time dashboards for educators/admins ✓ Data quality standards & model monitoring ✓ Stay updated on AI/ML in edtech Budget: ₹37,500 INR Timeline: 5 days Ready to drive student success!

@KALAIRAJ18

Hello, I am a skilled Data Scientist and Data Engineer with strong experience in Python, SQL, and building scalable data pipelines. I have hands-on experience in data cleaning, ETL development, exploratory data analysis, and machine learning model building. I have worked with structured and unstructured datasets and can deliver reliable, optimized, and well-documented solutions. I am comfortable working with cloud platforms and big data tools when required. I focus on delivering accurate results, clear communication, and on-time project completion. I am confident I can contribute effectively to your project requirements and provide high-quality data-driven solutions. I am ready to start immediately and discuss your project in detail.

@ishp9

I am a Data Scientist with strong hands-on experience in Python, SQL, and machine learning, focused on turning raw educational data into actionable, AI-driven insights. I have worked on data collection, cleaning, and analysis pipelines, built predictive models to forecast performance trends, and designed personalization logic to improve user engagement. .

@HarisAsif14

Hello, I’m excited about the opportunity to help transform Gradlynk into a more intelligent, AI-driven CRM. My goal is not just to build models, but to create a practical decision-support system that improves student engagement, predicts performance risks, and supports educators with clear, actionable insights. My approach would be: 1. Data Audit & Preparation Review and structure CRM data, identify key engagement signals (attendance, assignments, logins, communication), and implement data quality checks to ensure reliable modeling. 2. Predictive Modeling Develop models to forecast student performance risk, detect early disengagement, and support personalized learning pathways using Python-based ML tools (Scikit-learn/TensorFlow). I will prioritize explainable AI so predictions are transparent and educator-friendly. 3. Integration & Insights Work with your team to integrate models into Gradlynk and design KPI-focused dashboards that translate analytics into practical recommendations. What differentiates me is a structured ML pipeline (clean → validate → model → evaluate → deploy) and a strong focus on real-world usability. I also propose starting with a small Proof of Concept to demonstrate measurable value before scaling further. I would be glad to discuss your current data structure and top priority outcomes to align the AI roadmap with your strategic goals. Best regards, Haris

@manuj1808

Hello, I’m a Data Scientist with strong hands-on experience in Python, SQL, ML modeling, and applied analytics, and I’d be glad to help evolve Gradlynk into a more intelligent, AI-driven CRM platform. I focus on turning raw CRM and student-behavior data into deployable models and clear, decision-ready insights — not just experiments. I can support you with: • Data cleaning, feature engineering, and unified datasets from Gradlynk + external sources • Predictive models for student performance, engagement risk, and outcome forecasting • Personalization models for recommendations and student journey optimization • ML pipelines using Scikit-learn / PyTorch with reproducible training workflows • Dashboards and visualizations for educators and admins (Power BI / Python) • Production-ready SQL + Python data pipelines with validation checks Tech stack: Python, Pandas, Scikit-learn, TensorFlow/PyTorch, SQL, Power BI, cloud (AWS/GCP), API-based ML integration. I collaborate closely with product and ops teams and translate model outputs into practical actions and feature specs. Happy to review your Gradlynk schema and propose a concrete ML roadmap. if you want i can share you my github profile link. Thanks Manu Jain

@Clem2003

Je suis étudiant en master de mathématiques appliquées option statistique. Je dispose des compétences suivantes : *Programmation Python *Programmation R *Analyse de données *Conception de modèle statistique et prédiction Je serais ravi de participer à ce projet et aussi perfectionner mon niveau. Cordialement Ediman Kouassi.

@YashBhatt99

Hello Team, I’m a Data Scientist with strong expertise in Python, ML, and AI-driven product development. I can help transform Gradlynk into an intelligent CRM by building predictive models, improving data pipelines, and delivering actionable insights to enhance student engagement and operations. With experience integrating AI into real-world systems, I focus on scalable, business-focused solutions aligned with product and education goals. Best regards, Yash Bhatt

@gajendrat

I am a data analyst with a fresh and innovative perspective, currently completing my Data Analyst Internship. I hold a Bachelor's degree in Artificial Intelligence and Data Science engineering, equipping me with strong analytical skills and technical proficiency. My experience includes collaborating on data-driven projects, where I focus on transforming complex data into actionable insights. I excel in data visualization, statistical analysis, and using analytics tools to solve real-world problems. My goal is to help businesses make informed decisions by delivering precise analysis that drives growth. If you're looking for a motivated analyst who can bring a unique lens to your data challenges, let’s connect and discuss how I can support your project.

@dnyanesh2326

Hi, I have hands-on experience in data analysis, machine learning, and building end-to-end data pipelines using Python and SQL. I can help enhance Gradlynk by developing predictive models, personalizing student experiences, and translating complex insights into actionable recommendations for your business teams.

@walenchy

Dear Hiring Manager, I am excited to apply for the Data Scientist & Engineer position. With a strong foundation in data analysis, engineering principles, and problem-solving, I bring both analytical depth and practical implementation skills to every project I handle. My experience spans the full data lifecycle — from data collection and cleaning to modeling, deployment, and performance monitoring. I work comfortably with Python (Pandas, NumPy, Scikit-learn), SQL, and visualization tools such as Power BI and Matplotlib. On the engineering side, I design structured data pipelines, optimize queries, and ensure datasets are reliable, scalable, and production-ready. What sets me apart is my ability to bridge the gap between insight and execution. I don’t just build models; I focus on understanding business objectives and selecting the right metrics. I am detail-oriented, analytical, and committed to turning complex data into meaningful decisions. I would welcome the opportunity to discuss how I can contribute to your team. Best regards, Ibrahim Ramon

@vinayakparte5121

I am a Data Scientist specialized in Python, SQL, and Scikit-learn, ready to transform Gradlynk into a leading AI-driven EdTech platform. I offer a dual focus on technical rigur and business value: I will build predictive models to personalize student journeys and forecast performance while ensuring data integrity across your CRM. By translating complex analytics into clear recommendations, I help educators and stakeholders optimize engagement. My experience in building scalable cloud pipelines ensures that the AI features we develop are robust, reliable, and perfectly integrated into your existing ecosystem.

@jayachandug

I’m excited to apply for the Data Scientist role to help transform Gradlynk into an intelligent, AI-powered CRM that improves student engagement and learning outcomes. With strong experience in Python, SQL, and machine learning, I specialize in turning raw data into actionable insights and building predictive models that support data-driven decisions in education and product environments. I can collect, clean, and analyze data from multiple sources, design robust data pipelines, and develop predictive models for student performance forecasting, engagement scoring, and personalized learning recommendations. My workflow includes exploratory data analysis, feature engineering, model development (using Scikit-learn, TensorFlow, or PyTorch), and clear visualization dashboards for stakeholders. I also focus on data quality monitoring and reproducible analytics to ensure reliability across systems. I’ve worked on analytics dashboards, ML pipelines, and end-to-end data projects, and I’m comfortable collaborating with product and engineering teams to integrate AI features into real platforms. I communicate insights in a clear, business-friendly way so educators and administrators can make informed decisions. I would love to contribute to Gradlynk by building intelligent analytics features, predictive models, and dashboards that enhance student success and operational efficiency.