Identification of Heading and Heading Levels from HTML files

Quant Analyst (Analysis)

Intro

Energy markets are extremely dynamic. Therefore, our professionals in Wholesale trade 24 hours a day, 7 days a week to optimize portfolio returns and to mitigate market risks. Our focus is maximizing the extrinsic value of our assets (power plants, long-term contracts, gas pipelines and storage facilities, etc. ...) with our asset-backed trading strategy. In addition, we maximize profits through origination (structured deals) and proprietary trading activities. Furthermore, by supplying electricity and gas to B2B customers.

• Extensive knowledge in the field of quantitative models, methods and techniques.
• Thorough knowledge of (systematic) energy trading, complex energy contracts (structured products) and financial products (derivatives).
• Experience in pricing Structured Energy products.
• Experience building pricing models.
• Sound knowledge of the Electricity Imbalance System and the Day-ahead market.
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As a member of the Data Team, you will develop the data-driven solutions needed for the numeric transformation of Decathlon

• Build Cloud Data Pipeline : Design, build, test and deploy cutting edge analytics pipeline at Decathlon Sports India
• Data Ingestion : Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL ... and Big data technologies
• Data Integrity : Collaborate with Data Scientists and Business Intelligence Engineers (BIEs) to recognise and help adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation
• Productionization : Productionization of AI-ML models using Restful API?s Framework & process management, Dockerization, CI-CD etc.
• Software Engineering : Work across all phases of SDLC, and use Software Engineering principles to build scaled solutions. Object-oriented languages (e.g. Python, R, Java, C#, C++ ) and frameworks (e.g. J2EE or .NET)

• An expert capable of interpreting abstract data, apply mathematical algorithms on them to solve real-world problems. 
• Expert in prototyping traditional ML (GBMs, scikit, etc.) and AI frameworks (keras, tensorflow, mxnet, pytorch, etc.) for a variety of applications. 
• A clear and concise communicator, whether written or spoken. 
• Trained in a technical ...field with a B.S. degree in Computer Science, Math, Machine Learning, or similar field.

Must have skills

• 12+ years of overall experience.
  
• Machine Learning / Data Science
  
• NLP
  
• Linear regression, Logistic regression, Decision Tree, Random Forest & KNN
  
• Data Science, Statistical modelling, Predictive Modelling, ML and Modelling Tools
  
• Deep Learning
  
• Google Cloud is good to have if no good experience with Azure or AWS
  

As our Data Scientist, you will develop complex statistical models and machine learning algorithms to tackle critical product and business challenges. Working with the Product team, you will implement data science models that integrate into live production systems. Through deep behavioral analytics, you will yield significant product insights to help enhance our player experien ...ces. As a leader, you will level up our data science infrastructure and tools by contributing directly to our data intelligence vision and stack.

Responsibilities

• Derive insights from data and present them to relevant stakeholders to improve business KPIs.
• Select features and build and optimize classifiers using machine learning techniques.
• Propose hypotheses and design experiments in the context of specific problems.
• Mine data using state-of-the-art techniques.
• Extend the company?s data with third-party sources of information when needed.
• Find opportunities to automate analytics and data flow processes using machine learning algorithms, and work with the Technical team to save time and increase productivity.
• Process and cleanse data, and verify the integrity of data used for analysis.
• Conduct ad hoc analysis and present results in a clear manner.
• Create automated anomaly detection systems and constantly track their performance.
  
  

Qualifications

• 6+ years of experience in a Data Scientist role, with hands-on experience in all stages and processes of data science, including statistical model development, machine learning, analytics and data operations.
• Ability to yield clear, actionable insights that improve business KPIs.
• Advanced applied statistics skills, such as distributions, statistical testing, regression, etc.
• Expertise in identifying trends, patterns, and outliers in data.
• Experience in statistical programming languages using analytical packages/library: R, Python.
• Experience in data visualization tools, such as Tableau, ClickView, and PowerBI.
• Experience in enterprise data technologies, large-scale DB management, ETL pipelines, and streaming models. Proficiency in SQL and relational databases, data warehousing, and NoSQL databases.
• Experience in Hadoop, PIG, and HIVE preferred, though not mandatory.
• Experience in machine learning: data/text mining, NLP, decision trees, adaptive decision algorithms, random forest and search algorithms.
• Data-oriented thinking and scientific temperament that seeks to rigorously validate hypotheses/ideas.
• Must have a Ph.D. in Statistics/Optimization Algorithms/Artificial Intelligence/Machine Learning, or a similar domain.

About Junglee Games

Junglee Games is a leader in the skill-gaming space, with over 25 million users. Founded in San Francisco in 2012, and funded by top-tier Silicon Valley VCs, Junglee Games is the fastest-growing skill-gaming company in the world. Some of our notable games are Junglee Rummy, Eatme.io, Junglee Teen Patti, and Howzat.

With teams in 7 countries, Junglee is 250 people strong and has close to doubled in revenues and headcount every year. With YOY growth of 80-100% and high pro?tability, Junglee will see close to $600 million in gross transaction volumes in FY19-20 and scale to 50 million users.

Our team has worked on international AAA titles like Transformers, Real Steel, Mech Conquest, and Dueling Blades. Our designers have worked on some of Hollyw More

Looking for an individual who has experience in the Insurance/Banking sector as an underwriter and can work on building scorecards that can help assess the risk levels of farmers at a macro level. 

You will be working with client relationship managers, product owners and developers to generate understanding, strategy and suggest actions based on data. You will be a blend of data hacker, business analyst, coder, communicator and guide to translate terabytesof data into customer insights or usable solutions.
Pro-actively identify opportunities for application of analytics in the organi ...zationUnderstand organization’s analytical needs and convert business problems to analytical problems
Take full ownership of your work, from the initial idea-generation phase to the implementation of the final product to its maintenance and improvement–Execute/deliver projects independently
Transform large complex datasets fromvarious sources (transactional, digital, logs, campaigns..)
Give pragmatic, actionable business /consumer insightsin a well-presented manner
Workwith cutting edge tools like GreenPlum, R, Python etc. and arriveat the best approach to solve challenging problems
Hands-on coding, data manipulation, integration plus deployment to production systems
Create marketing plans or campaign ideas and derive ideal target groups for campaigns based on various call to actions
Develop and automate Business Intelligence frameworks
Develop new algorithms for predicting or influencing consumer behavior prediction(eg: next purchase, attrition etc.)–Build, validate and deploy into production
Create client-ready decks for final deliverablesand present the same if needed
Develop and deploy solutions / algorithms for data qualitymonitoring and data enrichment
Mastering the fast evolving data structure and infrastructure; Understanding constraints and troubleshooting to arrive at workarounds when required
Work on end-to-end data management including database design, data update processes, datapipeline set-up and enriching data quality
Understand and experiment with different statistical and machine learning algorithms and apply them for business problems
Challenge ideas and methods while working together with talented, highly skilled team members.
Independently define & solveproblems,research & development, self-learning and skill development
Interview for recruitment and guide other members in the department

You will be working with client relationship managers, product owners and developers to generate understanding, strategy and suggest actions based on data. You will be a blend of data hacker, business analyst, coder, communicator and guide to translate terabytes of data into customer insights or usable solutions.

• Pro-actively identify opportunities for application of analytics in ... the organization
• Understand organization’s analytical needs and convert business problems to analytical problems
• Take full ownership of your work, from the initial idea-generation phase to the implementation of the final product to its maintenance and improvement – Execute/deliver projects independently
• Transform large complex datasets from various sources (transactional, digital, logs, campaigns..)
• Give pragmatic, actionable business / consumer insights in a well-presented manner
• Work with cutting edge tools like GreenPlum, R, Python etc. and arrive at the best approach to solve challenging problems
• Hands-on coding, data manipulation, integration plus deployment to production systems
• Create marketing plans or campaign ideas and derive ideal target groups for campaigns based on various call to actions
• Develop and automate Business Intelligence frameworks
• Develop new algorithms for predicting or influencing consumer behavior prediction (eg: next purchase, attrition etc.) – Build, validate and deploy into production
• Create client-ready decks for final deliverables and present the same if needed
• Develop and deploy solutions / algorithms for data quality monitoring and data enrichment
• Mastering the fast evolving data structure and infrastructure; Understanding constraints and troubleshooting to arrive at workarounds when required
• Work on end-to-end data management including database design, data update processes, data pipeline set-up and enriching data quality
• Understand and experiment with different statistical and machine learning algorithms and apply them for business problems
• Challenge ideas and methods while working together with talented, highly skilled team members.
• Independently define & solve problems, research & development, self-learning and skill development
• Interview for recruitment and guide other members in the department