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Data Scientist, Cloud Solution Architect, Machine Learning Algorithm Research Engineer, Kaggle Competition Expert #553 (Top 0.5 %), with extensive experience with developing algorithms, statistical models and deep learning architectures using Python in a Big Data environment. Currently working as a Data Scientist with TimeSeries (IoT) domain, design machine learning experiments and developing efficient sequence models for Time-Series segmentation and classification. I have 8+ yrs. experience with Data Science & AI challenges. • A developer and researcher with expertise in data mining , visualization, modeling and evaluation using Python, Pyspark or R on Cloud Platforms. Intermediate experience with SQL and Java. • Curious and enthusiastic to learn and adapt new ideas, concepts, methods, and technology • Experienced with solving variety of interdisciplinary data problems, designing and managing algorithms/models and data science APIs in cloud based scalable way • Interested in sequence modeling for TimeSeries, NLP, Computer Vision and discrete optimization in biomedical, IT product, operation research, supply chain, or energy domain #DataScientist #MachineLearningEngineer #CloudArchitecture #DataEngineer #SoftwareEngineer #DataScienceConsultant #ResearcherAndAnalyst ✆ Contact at minesh[dot]1291@gmail.com for Consultancy or Positions
• Expert full-stack Python & JavaScript developer • Full DevOps: project architecture to production deployment at scale (whether VMs, Docker containers, cloud services, or on-prem) • Outstanding trouble-shooter and "OMG! Everything is on fire! HALP!!" first responder • Strong web app, data structures, data science, and visualization skills • Enjoy complex integration and automation challenges • Love mentoring. Half-price ($60/hr) for all genuine students
** Full refund if I fail to solve the problem.** Experienced Software Architect, Data Scientist and a polyglot programmer with 9+ years of experience in writing production software code using NodeJS, Go, C# .NET, Python, R, JavaScript, Java, C/C++, and others . In my stint at Research Lab, I worked on building Chatbots, Augmented Reality powered apps, Data Science and Machine Learning. I love explaining complicated things in the most simple way.
Data Scientist with 8+ years of experience working on all types of data related problems using Python, SQL, R and Excel. I am working as a _Lead Data Scientist_ in TCS (one of the word's largest service-based company). I am also a co-founder of Van Braun, an Artificial Intelligence based company which works on advance NLP modules **U.S. Patent holder**
Love to create products which enable smarter/automated decision-making using data at scale. I like going into new areas and tackling problems that can be solved by applying data science.
Rust Senior developer & CTO. From Fullstack engineer, to system and protocol programming with Rust. I have created a few large projects with rust, all are currently running in production, and converting all past projects into... Rust as well ;) I live rust, i breath rust, and I eat rust for breakfast.
I'm the founder of TryNewAI, an AI-native engineering firm helping AI-native startups and pharma R&D teams ship production AI through embedded senior engineers. Before TryNewAI, I spent six years as a senior software engineer at IPsoft, Justdial, and InMobi, building production systems across enterprise AI, search, and ad-tech. Those years taught me what most AI projects miss: getting something to work in a notebook is a different problem from making it work reliably in production, at scale, on dirty real-world data. I founded TryNewAI in 2020 to focus on exactly that gap. Not staff augmentation. Not throw-it-over-the-wall projects. Instead, embedded engineering: senior engineers placed inside client teams, picking the highest-value AI workflows alongside leadership, and shipping them to production end-to-end. Five years in, the model has held up: → ForwardEdgeAI - what began as a 3-month contract is now a 5-year continuous engagement → Pharma & life sciences - production AI and data engineering with Johnson & Johnson, Charles River Labs, and Haleon → Enterprise - engineering work with Cisco and AusNet → AI-native startups — including Ox.work (San Francisco) Where I personally go deep: * Taking AI systems from prototype to production - eval harnesses, observability, reliability engineering * Data engineering for AI - pipelines, foundations, AI-ready data architectures * Regulated environments - pharma R&D, GxP contexts where "usually works" isn't acceptable * Embedded leadership - working as a fractional senior engineer or tech lead inside client teams Who I'm best for: -> A CTO at an AI-native startup whose AI features are stuck between prototype and production. A pharma R&D leader trying to operationalize AI inside regulated workflows ->A founder who'd rather have one senior engineer in the trenches than a five-person dev shop behind a project wall. Hyderabad-based, working globally. DMs open — happy to talk shop even if it doesn't lead to an engagement.
**DevOps & MLOps Engineer | Cloud Specialist (GCP, AWS, Azure)** DevOps and MLOps Engineer with 6+ years of remote experience designing and implementing cloud infrastructure across GCP, AWS, and Azure. Expert in building scalable web applications and AI/ML systems with comprehensive knowledge of 90+ cloud services. Proven track record delivering cost-optimized solutions for US and European clients while working fully remote since 2018. **Technical Skills** * Cloud Platforms: GCP (Expert), AWS (Expert), Azure (Proficient) * Infrastructure as Code: Terraform, CloudFormation, Google Cloud Deployment Manager * Containerization: Kubernetes (GKE, EKS, AKS), Docker, ECS, Cloud Run * CI/CD & DevOps Tools: Jenkins, Google Cloud Build, AWS CodePipeline, Azure DevOps, Ansible * Programming & Scripting: Python, Bash, YAML, HCL * Operating Systems Administration: Linux (Ubuntu, Debian, CentOS), Solaris **Cloud Expertise** **(a) GCP Services/Skills** * Compute & Containers: Compute Engine, GKE, Cloud Run, App Engine, Batch, Cloud Functions * AI/ML Platform: Vertex AI, Document AI, Gemini, Vision AI, Speech AI, NotebookLM * Data & Analytics: BigQuery, Dataflow, Pub/Sub, Dataproc, Composer, Looker * Storage & Databases: Cloud SQL (MySQL, PostgreSQL), Firestore, Bigtable, Memorystore, Cloud Storage, Filestore * Networking: VPC, Load Balancing, Cloud CDN, Cloud DNS, Cloud NAT, Interconnect, VPN * DevOps & CI/CD: Cloud Build, Artifact Registry, Container Registry, Cloud Deploy, Source Repositories * Serverless & Integration: Cloud Functions, Cloud Scheduler, Cloud Tasks, Workflows, API Gateway, Apigee * Observability: Cloud Monitoring, Logging, Trace, Error Reporting * Security & Management: IAM, Organizations, Security Command Center, Deployment Manager **(b) AWS Services/Skills** * Compute & Containers: EC2, ECS, EKS, Lambda, Batch, Elastic Beanstalk, Lightsail * AI/ML Service: SageMaker, Polly, Rekognition * Storage & Databases: S3, EFS, RDS, DynamoDB, ElastiCache, DocumentDB, MemoryDB, AWS Backup * Networking & CDN: VPC, CloudFront, API Gateway, Route 53, WAF & Shield * DevOps & Developer Tools: CodePipeline, CodeBuild, CodeDeploy, CodeCommit, CodeArtifact * Management/Governance: CloudWatch, CloudFormation, CloudTrail, AWS Config, Organizations, Trusted Advisor * Security & Compliance: IAM, KMS, Certificate Manager, Secrets Manager * Application Integration: SQS, SNS, Step Functions, Amazon MQ, SES * IoT & Edge: IoT Core, IoT Events * Cost Management: Billing Conductor, Cost Explorer **(c) Azure Services/Skills** * Compute & Containers: Virtual Machines, AKS, Azure Container Registry, Container Storage * Databases: Azure SQL, Azure Cache for Redis * DevOps: Azure DevOps * Networking: Azure Firewall, NAT Gateway, Load Balancer, Virtual Network * Storage: Blob Storage, Disk Storage, Container Storage, Storage Accounts **Cloud Certifications** * Google Professional Cloud Architect by Google Cloud Platform (GCP) * Amazon Web Services Solutions Architect Associate by Amazon Web Services (AWS) **Professional Affiliations** * Member | AI Accelerator Institute | May 2023 - Present * Connecting and empowering AI infrastructure innovators * AWS Community Builder | Amazon Web Services | May 2021 - May 2023 * Built AWS Community through meetups, training, and live sessions **Additional Courses** **DevOps Courses (from LinuxAcademy)** * DevOps Essentials * Docker Quick Start / Docker Deep Dive * Using Ansible for CM and Deployments * Jenkins Quick Start / Jenkins and Build Automation * Container Clusters with Kubernetes * Puppet Quick Start * Learning Vagrant * Ansible Quick Start **Machine Learning Courses (From Coursera)** * Machine Learning with TensorFlow on GCP * How Google does Machine Learning * Art and Science of Machine Learning - Feature Engineering * Intro to TensorFlow * Launching into Machine Learning **Data Science Courses (From DataCamp)** * Cleaning Data in Python * Data Manipulation * Data Scientist with Python * Importing & Cleaning Data with Python * Importing Data in Python (Part 1 & 2) * Intermediate Python for Data Science * Intro to Python for Data Science * Introduction to Databases in Python * Machine Learning with Python * Python Data Science Toolbox **Some Recent Projects and Technologies** * Deployment and Maintenance of GKE Clusters in Development, Staging and Production Environments * Scripting deployment of a complete Project with GKE in GCP * Scripting/Terraforming deployment of a complete infrastructure in AWS * Terraforming App Engine, Cloud SQL, MongoDB, VMs and MemoryStore in GCP * Migration to Google Cloud Platform, with web application, databases and storage * Setting up number of GKE clusters for clients for online services * Setup of multiple projects for DICOM services for a US client * Setup of ML Based services infrastructure using GKE (with GPUs) and VMs
An experienced data scientist and full stack developer. My key skills are - Python, machine learning, data engineering. And ofcourse, raspberry PIs. :)
I am Shubham Dokania, Ex-Research Scientist at Mercedes-Benz R&D. My main area of work includes, but not limited to, deep learning for computer vision and artificial intelligence. https://shubham1810.github.io
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