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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

 

#LI-Remote

Role - Data Scientist / Machine Learning Scientist / Deep Learning Engineer -: 3 - 5 yrs experienced Programming Must Know:- Python, Tensorflow, Keras, Kafka, Spark Must have worked in Video Analytics with at least 2 Deep Learning Models like R-CNN, LSTM, Object Detection Models like YOLO, Object tracking Models like Deep SORT Must have good model training and testing experience with Structured(statistical machine learning) and Unstructured Data Must be good with Statistics. Good to have Data visualization experience in Python or any data visualization tool. Good to have Kubernetes, Multiprocessing experience, MLops like docker, hydra etc

Team:- We are a team of 9 data scientists working on Video Analytics Projects, Data Analytics projects for internal AI requirements of Reliance Industries as well for the external business. At a time, we make progress on multiple projects(atleast 4) in Video Analytics or Data Analytics.

Responsibilities

• Work on execution and scheduling of all tasks related to assigned projects' deliverable dates
• Optimize and debug existing codes to make them scalable and improve performance
• Design, development, and delivery of tested code and machine learning models into production environments
• Work effectively in teams, managing and leading teams
• Provide effective, constructive feedback to the delivery leader
• Manage client expectations and work with an agile mindset with machine learning and AI technology
• Design and prototype data-driven solutions

Eligibility

• Highly experienced in designing, building, and shipping scalable and production-quality machine learning algorithms in the field of Python applications
• Working knowledge and experience in NLP core components (NER, Entity Disambiguation, etc.)
• In-depth expertise in Data Munging and Storage (Experienced in SQL, NoSQL, MongoDB, Graph Databases)
• Expertise in writing scalable APIs for machine learning models
• Experience with maintaining code logs, task schedulers, and security
• Working knowledge of machine learning techniques, feed-forward, recurrent and convolutional neural networks, entropy models, supervised and unsupervised learning
• Experience with at least one of the following: Keras, Tensorflow, Caffe, or PyTorch

About Us:

We are a VC-funded startup solving one of the biggest transportation problems India faces. Most passengers in India travel long distance by IRCTC trains. At time of booking, approx 1 out of every 2 passengers end up with a Waitlisted or RAC ticket. This creates a lot of anxiety for passengers, as Railway only announces only 4 hour before departure if they have a confirmed seat. We solve this problem through our Waitlist & RAC Protection. Protection can be bought against each IRCTC ticket at time of booking. If train ticket is not confirmed, we fly the passenger to the destination. Our team consists of 3 Founders from IIT, IIM and ISB.

Functional Experience:

• Computer Science or IT Engineering background with solid understanding of basics of Data Structures and Algorithms
• 2+ years of data science experience working with large datasets
• Expertise in Python packages like pandas, numPy, sklearn, matplotlib, seaborn, keras and tensorflow
• Expertise in Big Data technologies like Hadoop, Cassandra and PostgreSQL
• Expertise in Cloud computing on AWS with EC2, AutoML, Lambda and RDS
• Good knowledge of Machine Learning and Statistical time series analysis (optional)
• Unparalleled logical ability making you the go to guy for all things related to data
• You love coding like a hobby and are up for a challenge!

 

Cultural:

• Assume a strong sense of ownership of analytics : Design, develop & deploy
• Collaborate with senior management, operations & business team
• Ensure Quality & sustainability of the architecture
• Motivation to join an early stage startup should go beyond compensation

Data Sutram, funded by India Infoline (IIFL), Indian Angel Network (IAN) and 100x.VC (led by Sanjay Mehta), is an alternate data company, using external data feeds to create every location's DNA that is utilized in various use cases like credit underwriting, location profiling, site selection, etc. It is one of the fastest-growing companies in the space of Artificial Intelligence & Location Analytics in India. As a data scientist, you get to work in our core product and work on various critical client use cases. As a data scientist, you get to explore new solutions and use cases collaborating with Business Analysts & fellow Data Scientists.

Roles and Responsibilities

• Managing available resources such as hardware, data, and personnel so that deadlines are met.
• Analyzing the ML and Deep Learning algorithms that could be used to solve a given problem and ranking them by their success probabilities
• Exploring data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
• Defining validation framework and establish a process to ensure acceptable data quality criteria are met
• Supervising the data acquisition and partnership roadmaps to create stronger product for our customers.
• Defining feature engineering process to ensure usage of meaningful features given the business constraints which may vary by market
• Device self-learning strategies through analysis of errors from the models
• Understand business issues and context, devise a framework for solving unstructured problems and articulate clear and actionable solutions underpinned by analytics.
• Manage multiple projects simultaneously while demonstrating business leadership to collaborate & coordinate with different functions to deliver the solutions in a timely, efficient and effective manner.
• Manage project resources optimally to deliver projects on time; drive innovation using residual resources to create strong solution pipeline; provide direction, coaching & training, feedbacks to project team members to enhance performance, support development and encourage value aligned behaviour of the project team members; Provide inputs for periodic performance appraisal of project team members.

 

Preferred Technical & Professional expertise

• Undergraduate Degree in Computer Science / Engineering / Mathematics / Statistics / economics or other quantitative fields
• At least 2+ years of experience of managing Data Science projects with specializations in Machine Learning
• In-depth knowledge of cloud analytics tools.
• Able to drive Python Code optimization; ability review codes and provide inputs to improve the quality of codes
• Ability to evaluate hardware selection for running ML models for optimal performance
• Up to date with Python libraries and versions for machine learning; Extensive hands-on experience with Regressors; Experience working with data pipelines.
• Deep knowledge of math, probability, statistics and algorithms; Working knowledge of Supervised Learning, Adversarial Learning and Unsupervised learning
• Deep analytical thinking with excellent problem-solving abilities
• Strong verbal and written communication skills with a proven ability to work with all levels of management; effective interpersonal and influencing skills.
• Ability to manage a project team through effectively allocation of tasks, anticipating risks and setting realistic timelines for managing the expectations of key stakeholders
• Strong organizational skills and an ability to balance and handle multiple concurrent tasks and/or issues simultaneously.
• Ensure that the project team understand and abide by compliance framework for policies, data, systems etc. as per group, region and local standards

Key Accountability :

- Provide insights based on data to business teams

- Develop framework, solutions and recommendations for business problems

- Build ML models for predictive solutions

- Use advance data science techniques to build business solutions

- Automation / Optimization of new/existing models ensuring smooth,timely and accurate execution with lowest possible TAT.

- Design & maintenance of response tracking, measurement, and comparison of success parameters of various projects.

- Ability to handle large volumes of data with ease using multiple software like Python ,R etc

Experience in modeling techniques and hands on experience in building Logistic regression models, Random Forrest, K-mean Cluster, NLP, Decision tree, Boosting techniques etc


- Good at data interpretation and reasoning skills

4-6 years of total experience in data warehousing and business intelligence

3+ years of solid Power BI experience (Power Query, M-Query, DAX, Aggregates)

2 years’ experience building Power BI using cloud data (Snowflake, Azure Synapse, SQL DB, data lake)

Strong experience building visually appealing UI/UX in Power BI

Understand how to design Power BI solutions for performance (composite models, incremental refresh, analysis services)

Experience building Power BI using large data in direct query mode

Expert SQL background (query building, stored procedure, optimizing performance)

Role : 

• Understand and translate statistics and analytics to address business problems
• Responsible for helping in data preparation and data pull, which is the first step in machine learning
• Should be able to do cut and slice data to extract interesting insights from the data
• Model development for better customer engagement and retention
• Hands on experience in relevant tools like SQL(expert), Excel, R/Python
• Working on strategy development to increase business revenue

 

Requirements:

• Hands on experience in relevant tools like SQL(expert), Excel, R/Python
• Statistics: Strong knowledge of statistics
• Should able to do data scraping & Data mining
• Be self-driven, and show ability to deliver on ambiguous projects
• An ability and interest in working in a fast-paced, ambiguous and rapidly-changing environment
• Should have worked on Business Projects for an organization, Ex: customer acquisition, Customer retention.

Nactus is at forefront of education reinvention, helping educators and learner’s community at large through innovative solutions in digital era. We are looking for an experienced AI specialist to join our revolution using the deep learning, artificial intelligence.  This is an excellent opportunity to take advantage of emerging trends and technologies to a real-world difference.

 

Role and Responsibilities

• Manage and direct research and development (R&D) and processes to meet the needs of our AI strategy.
• Understand company and client challenges and how integrating AI capabilities can help create educational solutions.
• Analyse and explain AI and machine learning (ML) solutions while setting and maintaining high ethical standards.

 

Skills Required

 

• Knowledge of algorithms, object-oriented and functional design principles
• Demonstrated artificial intelligence, machine learning, mathematical and statistical modelling knowledge and skills.
• Well-developed programming skills – specifically in SAS or SQL and other packages with statistical and machine learning application, e.g. R, Python
• Experience with machine learning fundamentals, parallel computing and distributed systems fundamentals, or data structure fundamentals
• Experience with C, C++, or Python programming
• Experience with debugging and building AI applications.
• Robustness and productivity analyse conclusions.
• Develop a human-machine speech interface.
• Verify, evaluate, and demonstrate implemented work.
• Proven experience with ML, deep learning, Tensorflow, Python

About the job: - You will architect, code and deploy ML models (from scratch) to predict credit risk. - You will design, run, and analyze A/B and multivariate tests to test hypotheses aimed at optimizing user experience and portfolio risk. - You will perform data exploration and build statistical models on user behavior to discover opportunities for decreasing user defaults. And you must truly be excited about this part. - You’ll use behavioral and social data to gain insights into how humans make financial choices - You will spend a lot of time in building out predictive features from super sparse data sources. - You’ll continually acquire new data sources to develop a rich dataset that characterizes risk. - You will code, drink, breathe and live python, sklearn and pandas. It’s good to have experience in these but not a necessity - as long as you’re super comfortable in a language of your choice. About you: - You’ve strong computer science fundamentals - You’ve strong understanding of ML algorithms - Ideally, you have 2+ years of experience in using ML in industry environment - You know how to run tests and understand their results from a statistical perspective - You love freedom and hate being micromanaged. You own products end to end - You have a strong desire to learn and use the latest machine learning algorithms - It will be great if you have one of the following to share - a kaggle or a github profile - Degree in statistics/quant/engineering from Tier-1 institutes.

Requirement Specifications: Job Title:: Data Scientist Experience:: 7 to 10 Years Work Location:: Mumbai, Bengaluru, Chennai Job Role:: Permanent Notice Period :: Immediate to 60 days Job description: • Support delivery of one or more data science use cases, leading on data discovery and model building activities Conceptualize and quickly build POC on new product ideas - should be willing to work as an individual contributor • Open to learn, implement newer tools\products • Experiment & identify best methods\techniques, algorithms for analytical problems • Operationalize – Work closely with the engineering, infrastructure, service management and business teams to operationalize use cases Essential Skills • Minimum 2-7 years of hands-on experience with statistical software tools: SQL, R, Python • 3+ years’ experience in business analytics, forecasting or business planning with emphasis on analytical modeling, quantitative reasoning and metrics reporting • Experience working with large data sets in order to extract business insights or build predictive models • Proficiency in one or more statistical tools/languages – Python, Scala, R, SPSS or SAS and related packages like Pandas, SciPy/Scikit-learn, NumPy etc. • Good data intuition / analysis skills; sql, plsql knowledge must • Manage and transform variety of datasets to cleanse, join, aggregate the datasets • Hands-on experience running in running various methods like Regression, Random forest, k-NN, k-Means, boosted trees, SVM, Neural Network, text mining, NLP, statistical modelling, data mining, exploratory data analysis, statistics (hypothesis testing, descriptive statistics) • Deep domain (BFSI, Manufacturing, Auto, Airlines, Supply Chain, Retail & CPG) knowledge • Demonstrated ability to work under time constraints while delivering incremental value. • Education Minimum a Masters in Statistics, or PhD in domains linked to applied statistics, applied physics, Artificial Intelligence, Computer Vision etc. BE/BTECH/BSC Statistics/BSC Maths