11+ Statistical signal processing Jobs in India

Understanding business objectives and developing models that help to achieve them,
along with metrics to track their progress
Managing available resources such as hardware, data, and personnel so that deadlines
are met
Analysing the ML algorithms that could be used to solve a given problem and ranking
them by their success probability
Exploring and visualizing 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
Verifying data quality, and/or ensuring it via data cleaning
Supervising the data acquisition process if more data is needed
Defining validation strategies
Defining the pre-processing or feature engineering to be done on a given dataset
Defining data augmentation pipelines
Training models and tuning their hyper parameters
Analysing the errors of the model and designing strategies to overcome them
Deploying models to production

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

This role is primarily responsible for building AIML models and cognitive applications

Principal Accountabilities :

1. Good in communication and converting business requirements to functional requirements

2. Develop data-driven insights and machine learning models to identify and extract facts from sales, supply chain and operational data

3. Sound Knowledge and experience in statistical and data mining techniques: Regression, Random Forest, Boosting Trees, Time Series Forecasting, etc.

5. Experience in SOTA Deep Learning techniques to solve NLP problems.

6. End-to-end data collection, model development and testing, and integration into production environments.

7. Build and prototype analysis pipelines iteratively to provide insights at scale.

8. Experience in querying different data sources

9. Partner with developers and business teams for the business-oriented decisions

10. Looking for someone who dares to move on even when the path is not clear and be creative to overcome challenges in the data.

Job Responsibilities

• Design machine learning systems
• Research and implement appropriate ML algorithms and tools
• Develop machine learning applications according to requirements
• Select appropriate datasets and data representation methods
• Run machine learning tests and experiments
• Perform statistical analysis and fine-tuning using test results
• Train and retrain systems when necessary

 

Requirements for the Job

 

1. Bachelor’s/Master's/PhD in Computer Science, Mathematics, Statistics or equivalent field andmust have a minimum of 2 years of overall experience in tier one colleges 

1. Minimum 1 year of experience working as a Data Scientist in deploying ML at scale in production
2. Experience in machine learning techniques (e.g. NLP, Computer Vision, BERT, LSTM etc..) andframeworks (e.g. TensorFlow, PyTorch, Scikit-learn, etc.)

1. Working knowledge in deployment of Python systems (using Flask, Tensorflow Serving)
2. Previous experience in following areas will be preferred: Natural Language Processing(NLP) - Using LSTM and BERT; chatbots or dialogue systems, machine translation, comprehension of text, text summarization.
3. Computer Vision - Deep Neural Networks/CNNs for object detection and image classification, transfer learning pipeline and object detection/instance segmentation (Mask R-CNN, Yolo, SSD).

About RARA NOW :

• RaRa Now is revolutionizing instant delivery for e-commerce in Indonesia through data-driven logistics.

• RaRa Now is making instant and same-day deliveries scalable and cost-effective by leveraging a differentiated operating model and real-time optimization technology. RaRa makes it possible for anyone, anywhere to get same-day delivery in Indonesia. While others are focusing on - one-to-one- deliveries, the company has developed proprietary, real-time batching tech to do - many-to-many- deliveries within a few hours. RaRa is already in partnership with some of the top eCommerce players in Indonesia like Blibli, Sayurbox, Kopi Kenangan, and many more.

• We are a distributed team with the company headquartered in Singapore, core operations in Indonesia, and a technology team based out of India.

Future of eCommerce Logistics :

• Data driven logistics company that is bringing in same-day delivery revolution in Indonesia

• Revolutionizing delivery as an experience

• Empowering D2C Sellers with logistics as the core technology

About the Role :

• Create and maintain optimal data pipeline architecture,
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
• Work with stakeholders including the Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
• Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data systems.
• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
• Prior experience on working on Big Query, Redshift or other data warehouses

• Should act as a technical resource for the Data Science team and be involved in creating and implementing current and future Analytics projects like data lake design, data warehouse design, etc.
• Analysis and design of ETL solutions to store/fetch data from multiple systems like Google Analytics, CleverTap, CRM systems etc.
• Developing and maintaining data pipelines for real time analytics as well as batch analytics use cases.
• Collaborate with data scientists and actively work in the feature engineering and data preparation phase of model building
• Collaborate with product development and dev ops teams in implementing the data collection and aggregation solutions
• Ensure quality and consistency of the data in Data warehouse and follow best data governance practices
• Analyse large amounts of information to discover trends and patterns
• Mine and analyse data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.\

• Bachelor’s or Masters in a highly numerate discipline such as Engineering, Science and Economics
• 2-6 years of proven experience working as a Data Engineer preferably in ecommerce/web based or consumer technologies company
• Hands on experience of working with different big data tools like Hadoop, Spark , Flink, Kafka and so on
• Good understanding of AWS ecosystem for big data analytics
• Hands on experience in creating data pipelines either using tools or by independently writing scripts
• Hands on experience in scripting languages like Python, Scala, Unix Shell scripting and so on
• Strong problem solving skills with an emphasis on product development.
• Experience using business intelligence tools e.g. Tableau, Power BI would be an added advantage (not mandatory)

Must-Have Skills:

• Extract and present valuable information from data
• Understand business requirements and generate insights
• Build mathematical models, validate and work with them
• Explain complex topics tailored to the audience
• Validate and follow up on results
• Work with large and complex data sets
• Establish priorities with clear goals and responsibilities to achieve a high level of performance.
• Work in an agile and iterative manner on solving problems
• Evaluate different options proactively and the ability to solve problems in an innovative way. Develop new solutions or combine existing methods to create new approaches.
• Good understanding of Digital & analytics
• Strong communication skills, orally and in writing

Job Overview:

As a Data Scientist, you will work in collaboration with our business and engineering people, on creating value from data. Often the work requires solving complex problems by turning vast amounts of data into business insights through advanced analytics, modeling, and machine learning. You have a strong foundation in analytics, mathematical modeling, computer science, and math - coupled with a strong business sense. You proactively fetch information from various sources and analyze it for better understanding of how the business performs. Furthermore, you model and build AI tools that automate certain processes within the company. The solutions produced will be implemented to impact business results.

About the Company:

 It is a Data as a Service company that helps businesses harness the power of data. Our technology fuels some of the most interesting big data projects of the word. We are a small bunch of people working towards shaping the imminent data-driven future by solving some of its fundamental and toughest challenges. 

 

 

Role: We are looking for an experienced team lead to drive data acquisition projects end to end. In this role, you will be working in the web scraping team with data engineers, helping them solve complex web problems and mentor them along the way. You’ll be adept at delivering large-scale web crawling projects, breaking down barriers for your team and planning at a higher level, and getting into the detail to make things happen when needed.  

 

Responsibilities  

•  Interface with clients and sales team to translate functional requirements into technical requirements 
•  Plan and estimate tasks with your team, in collaboration with the delivery managers 
•  Engineer complex data acquisition projects 
•  Guide and mentor your team of engineers 
•  Anticipate issues that might arise and proactively consider those into design 
•  Perform code reviews and suggest design changes 

 

 

Prerequisites 

•  Between 5-8 years of relevant experience 
• Fluent programming skills and well-versed with scripting languages like Python or Ruby 
• Solid foundation in data structures and algorithms 
• Excellent tech troubleshooting skills 
• Good understanding of web data landscape 
• Prior exposure to DOM, XPATH and hands on experience with selenium/automated testing is a plus 

 

Skills and competencies 

• Prior experience with team handling and people management is mandatory 
• Work independently with little to no supervision 
• Extremely high attention to detail  
•  Ability to juggle between multiple projects  

We are a nascent quantitative hedge fund led by an MIT PhD and Math Olympiad medallist, offering opportunities to grow with us as we build out the team. Our fund has  world class investors and big data experts as part of the GP,  top-notch ML experts as advisers to the fund, plus has equity funding to grow the team, license data and scale the data processing.

We are interested in researching and taking in live a variety of quantitative strategies based on historic and live market data, alternative datasets, social media data (both audio and video) and stock fundamental data.

You would join, and, if qualified, lead a growing team of data scientists and researchers, and be responsible for a complete lifecycle of quantitative strategy implementation and trading.

Requirements:

• Atleast 3 years of relevant ML experience
• Graduation date : 2018 and earlier
•   3-5 years of experience in high level Python programming.
• Master Degree (or Phd) in quantitative disciplines such as Statistics, Mathematics, Physics, Computer Science in top universities.
•   Good knowledge of applied and theoretical statistics, linear algebra and machine learning techniques. 
•   Ability to leverage financial and statistical insights to research, explore and harness a large collection of quantitative strategies and financial datasets in order to build strong predictive models.
• Should take ownership for the research, design, development and implementation of the strategy development and effectively communicate with other team mates
•   Prior experience and good knowledge of lifecycle and pitfalls of algorithmic strategy development and modelling. 
•   Good practical knowledge in understanding financial statements, value investing, portfolio and risk management techniques.
•   A proven ability to lead and drive innovation to solve challenges and road blocks in project completion.
• A valid Github profile with some activity in it

Bonus to have:

•   Experience in storing and retrieving data from large and complex time series databases
•   Very good practical knowledge on time-series modelling and forecasting (ARIMA, ARCH and Stochastic modelling)
•   Prior experience in optimizing and back testing quantitative strategies, doing return and risk attribution, feature/factor evaluation. 
•   Knowledge of AWS/Cloud ecosystem is an added plus (EC2s, Lambda, EKS, Sagemaker etc.) 
•   Knowledge of REST APIs and data extracting and cleaning techniques 
•   Good to have experience in Pyspark or any other big data programming/parallel computing
•   Familiarity with derivatives, knowledge in multiple asset classes along with Equities.
•   Any progress towards CFA or FRM is a bonus
• Average tenure of atleast 1.5 years in a company

Title: Analyst - Business AnalyticsExperience: 1 - 4 YearsLocation: ChennaiOpen Positions: 17Job Description:Roles & Responsibilities:- Designing and implementing analytical projects that drive business goals and decisions leveraging structured and unstructured data.- Generating a compelling story from insights and trends in a complex data environment.- Working shoulder-to-shoulder with business partners to come up with creative approaches to solve the business problem.- Creating dashboards for business heads by exploring available data assets.Qualifications:- Overall 1+ Years of Business Analytics experience with strong communication skills.- Bachelor or Master degree in computer science is preferred.- Excellent problem solving and client orientation skills.Skills Required:- Ability to program in Advanced SQL is must.- Hands-on experience in Modeling tools such as R or Python- Experience in Visualization tools such as Power BI, Tableau, Looker, etc., would be a big plus.- Analytics certifications from recognized platforms would be a plus - Udemy, Coursera, EDX,etc.

Preferred candidates : IIT/BITS/NIT Education : B.Tech/Master in Statistics/Economics/Mathematics- or any other quant discipline. - MBA's with Bachelors in any quant discipline JD : - Hands on experience with credit risk scorecard development. - Experience in developing statistical segmentation (CHAID, Cluster Analysis, SVM, Random Forest, Gradient Boosting etc)" - Strong proficiency in using SAS (Essential), R, Python (Preferred) - Generic - Understand the business problem and transform it into a statistical solutions structure -Collaborate with various dept heads and understand business priorities which can be addressed using advanced analytics