3+ Statistical Modeling Jobs in Mumbai | Statistical Modeling Job openings in Mumbai

Job Description

We are looking for an experienced engineer to join our data science team, who will help us design, develop, and deploy machine learning models in production. You will develop robust models, prepare their deployment into production in a controlled manner, while providing appropriate means to monitor their performance and stability after deployment.

 

What You’ll Do will include (But not limited to):

• Preparing datasets needed to train and validate our machine learning models
• Anticipate and build solutions for problems that interrupt availability, performance, and stability in our systems, services, and products at scale.
• Defining and implementing metrics to evaluate the performance of the models, both for computing performance (such as CPU & memory usage) and for ML performance (such as precision, recall, and F1)
• Supporting the deployment of machine learning models on our infrastructure, including containerization, instrumentation, and versioning
• Supporting the whole lifecycle of our machine learning models, including gathering data for retraining, A/B testing, and redeployments
• Developing, testing, and evaluating tools for machine learning models deployment, monitoring, retraining.
• Working closely within a distributed team to analyze and apply innovative solutions over billions of documents
• Supporting solutions ranging from rule-bases, classical ML techniques  to the latest deep learning systems.
• Partnering with cross-functional team members to bring large scale data engineering solutions to production
• Communicating your approach and results to a wider audience through presentations

Your Qualifications:

• Demonstrated success with machine learning in a SaaS or Cloud environment, with hands–on knowledge of model creation and deployments in production at scale
• Good knowledge of traditional machine learning methods and neural networks
• Experience with practical machine learning modeling, especially on time-series forecasting, analysis, and causal inference.
• Experience with data mining algorithms and statistical modeling techniques for anomaly detection in time series such as clustering, classification, ARIMA, and decision trees is preferred.
• Ability to implement data import, cleansing and transformation functions at scale
• Fluency in Docker, Kubernetes
• Working knowledge of relational and dimensional data models with appropriate visualization techniques such as PCA.
• Solid English skills to effectively communicate with other team members

 

Due to the nature of the role, it would be nice if you have also:

• Experience with large datasets and distributed computing, especially with the Google Cloud Platform
• Fluency in at least one deep learning framework: PyTorch, TensorFlow / Keras
• Experience with No–SQL and Graph databases
• Experience working in a Colab, Jupyter, or Python notebook environment
• Some experience with monitoring, analysis, and alerting tools like New Relic, Prometheus, and the ELK stack
• Knowledge of Java, Scala or Go-Lang programming languages
• Familiarity with KubeFlow
• Experience with transformers, for example the Hugging Face libraries
• Experience with OpenCV

 

About Egnyte

In a content critical age, Egnyte fuels business growth by enabling content-rich business processes, while also providing organizations with visibility and control over their content assets. Egnyte’s cloud-native content services platform leverages the industry’s leading content intelligence engine to deliver a simple, secure, and vendor-neutral foundation for managing enterprise content across business applications and storage repositories. More than 16,000 customers trust Egnyte to enhance employee productivity, automate data management, and reduce file-sharing cost and complexity. Investors include Google Ventures, Kleiner Perkins, Caufield & Byers, and Goldman Sachs. For more information, visit www.egnyte.com

 

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What you need to have:

 

About us: Quantiphi is a category defining Data Science and Machine Learning Software and Services Company focused on helping organizations translate the big promise of Big Data & Machine Learning technologies into quantifiable business impact. We were founded on the belief that machine learning and artificial intelligence are transformative technologies that will create the next quantum gain in customer experience and unit economics of businesses. Quantiphi helps clients find and capture hidden value from data through a unique blend of business acumen, big-data, machine learning and intuitive information design. AthenasOwl (AO) is our “AI for Media” solution that helps content creators and broadcasters to create and curate smarter content. We launched the product in 2017 as an AI-powered suite meant for the media and entertainment industry. Clients use AthenaOwl's context adapted technology for redesigning content, taking better targeting decisions, automating hours of post-production work and monetizing massive content libraries. Please Find Attached fact sheet for your reference. For more details visit: www.quantiphi.com ; www.athenasowl.tv Job Description: -Developing high-level solution architecture related to different use-cases in the media industry -Leveraging both structured and unstructured data from external sources and our proprietary AI/ML models to build solutions and workflows that can be used to give data driven insights. -Develop sophisticated yet easy to digest interpretations and communicate insights to clients that lead to quantifiable business impact. -Building deep relationship with clients by understanding their stated but more importantly, latent needs. -Working closely with the client-side delivery managers to ensure a seamless communication and delivery cadence. Essential Skills and Qualifications: -Hands-on experience with statistical tools and techniques in Python -Great analytical skills, with expertise in analytical toolkits such as Logistic Regression, Cluster Analysis, Factor Analysis, Multivariate Regression, Statistical modelling, predictive analysis. -Advanced knowledge of supervised and unsupervised machine learning algorithms like Random Forest, Boosting, SVM, Neural Networks, Collaborative filtering etc. -Ability to think creatively and work well both as part of a team and as an individual contributor -Critical eye for the quality of data and strong desire to get it right -Strong communication skills. -Should be able to read a paper and quickly implement ideas from scratch. -A pleasantly forceful personality and charismatic communication style.