Penjualan Big Data Jobs

Sr. Data Science Engineer Experience: 4–6 Years Location: Remote Shift: 1:30 PM – 10:30 PM IST Role Overview: We are seeking a skilled Sr. Data Science Engineer with expertise in Python, AWS, machine learning, and statistical modelling. The ideal candidate will drive end-to-end ML development, perform advanced data analysis, build scalable data pipelines, and deploy models in cloud environments. Key Responsibilities: Design, build, and deploy ML models using Python and AWS SageMaker. Perform exploratory data analysis (EDA) and generate actionable business insights. Develop and maintain ETL pipelines, data ingestion, transformation, and validation processes. Manage model versioning and experiment tracking using MLflow. Collaborate through GitHub code reviews and maintain hig...

Cuento con experiencia en programación y deseo llevar mis habilidades de análisis de datos al siguiente nivel. Necesito que un especialista me capacite de forma práctica y estructurada en migración de datos hacia la nube, con enfoque intermedio y usando exclusivamente AWS, la plataforma que ya manejo. Lo que busco: • Sesiones guiadas, en línea, donde revisemos casos reales de migración de bases de datos y procesos ETL desde entornos on-premise a S3, EMR, Athena y DynamoDB. • Explicación paso a paso y mejores prácticas con SQL Server, Integration Services y Analysis Services para preparar los datos antes de moverlos. • Ejemplos de scripts en Python y R que automaticen validaciones y transformaciones dentro de Spark....

I’m in the early stages of launching a new enterprise and I have a sizeable set of financial data that needs a fresh pair of eyes. The objective is straightforward: dig deep into the numbers, spot hidden patterns I can act on, and highlight anything unusual that could influence my next strategic move. You’ll receive raw transaction tables along with a brief on the business model. Using Python (think pandas, NumPy, maybe a touch of scikit-learn for exploratory modelling) and solid SQL querying, I’d like you to clean the data, explore relationships, and surface any trends or anomalies that aren’t obvious at first glance. Clear commentary in well-structured Jupyter notebooks or a similar environment is preferred so I can follow the logic step by step. By the end, I n...

I’m kicking off a predictive analytics programme for an IT-focused business unit in Pune and need an experienced AI consultant who can wear the architect’s hat from day one. You’ll guide the full lifecycle: shaping the use-cases with stakeholders, auditing our existing data assets, then designing a scalable machine-learning stack that can move from PoC to production without rewrites. I expect you to be comfortable choosing the right mix of Python, scikit-learn, PyTorch or TensorFlow, setting up automated training pipelines, and wiring everything into a cloud environment (AWS, Azure or GCP—whichever best fits the roadmap we draft together). Strong MLOps habits, version-controlled experiments and CI/CD for models are must-haves because this project must be repeatable...

We are looking for a highly skilled Senior Data Engineer with 8+ years of experience in designing, developing, and modernizing enterprise-scale data platforms. The ideal candidate should have strong expertise in Google Cloud Platform (GCP) and hands-on experience building scalable data pipelines, data migration, and modernization initiatives. Key Responsibilities Design, develop, and optimize end-to-end data pipelines on Google Cloud Platform (GCP). Build and maintain scalable ETL/ELT solutions using GCP services such as BigQuery, Dataflow, Dataproc, Cloud Storage, Pub/Sub, and Composer. Lead data modernization and migration projects from legacy/on-premise systems to GCP. Implement data integration, transformation, and orchestration processes for large-scale datasets. Ensure data quality,...

The Data Engineer is responsible for designing, constructing, and maintaining the systems and infrastructure required to process and analyze large volumes of data. This role will work closely with data scientists, analysts, and other stakeholders to ensure data is collected, stored, and processed efficiently. The Data Engineer will also develop and implement data pipelines, perform data quality checks, and optimize data storage and retrieval. Develop and maintain KPIs, metrics, and dashboards by leveraging diverse datasets. Ensure data quality and integrity through data validation, cleansing, and error handling. Design and implement back-end processes using data warehouse modeling techniques. Build and optimize ELT pipelines to capture and transform data for analytics and reporting. P...

I’m working on my graduate-level capstone and have chosen to build a full-fledged recommendation system using a publicly available dataset (e.g., MovieLens, Amazon Reviews, Goodreads—whichever fits best once we outline the approach). The end goal is to demonstrate solid grasp of modern recommender techniques, from data preprocessing through model training, evaluation, and an easy-to-showcase demo. Scope of work The project has three pillars: 1. Data pipeline – ingest, clean, and transform the chosen public dataset so it’s ready for modelling while remaining fully reproducible (Python, pandas, SQL or Spark if scale requires). 2. Modelling – experiment with at least two algorithms that illustrate contrasting paradigms, for example matrix factorization (Su...