Data Analyst

LogiNext is looking for a technically savvy and passionate Principle Engineer - Data Science to analyze large amounts of raw information to find patterns that will help improve our company. We will rely on you to build data products to extract valuable business insights.

In this role, you should be highly analytical with a knack for analysis, math and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine-learning and research.

Your goal will be to help our company analyze trends to make better decisions. Without knowledge of how the software works, data scientists might have difficulty in work. Apart from experience in developing R and Python, they must know modern approaches to software development and their impact. DevOps continuous integration and deployment, experience in cloud computing are everyday skills to manage and process data.

Responsibilities :

Adapting and enhancing machine learning techniques based on physical intuition about the domain Design sampling methodology, prepare data, including data cleaning, univariate analysis, missing value imputation, , identify appropriate analytic and statistical methodology, develop predictive models and document process and results Lead projects both as a principal investigator and project manager, responsible for meeting project requirements on schedule and on budget Coordinate and lead efforts to innovate by deriving insights from heterogeneous sets of data generated by our suite of Aerospace products Support and mentor data scientists Maintain and work with our data pipeline that transfers and processes several terabytes of data using Spark, Scala, Python, Apache Kafka, Pig/Hive & Impala Work directly with application teams/partners (internal clients such as Xbox, Skype, Office) to understand their offerings/domain and help them become successful with data so they can run controlled experiments (a/b testing) Understand the data generated by experiments, and producing actionable, trustworthy conclusions from them Apply data analysis, data mining and data processing to present data clearly and develop experiments (ab testing) Work with development team to build tools for data logging and repeatable data tasks tol accelerate and automate data scientist duties

Requirements:

Bachelor’s or Master’s degree in Computer Science, Math, Physics, Engineering, Statistics or other technical field. PhD preferred 8 to 10 years of experience in data mining, data modeling, and reporting 5+ years of experience working with large data sets or do large scale quantitative analysis Expert SQL scripting required Development experience in one of the following: Scala, Java, Python, Perl, PHP, C++ or C# Experience working with Hadoop, Pig/Hive, Spark, MapReduce Ability to drive projects Basic understanding of statistics – hypothesis testing, p-values, confidence intervals, regression, classification, and optimization are core lingo Analysis - Should be able to perform Exploratory Data Analysis and get actionable insights from the data, with impressive visualization. Modeling - Should be familiar with ML concepts and algorithms; understanding of the internals and pros/cons of models is required. Strong algorithmic problem-solving skills Experience manipulating large data sets through statistical software (ex. R, SAS) or other methods Superior verbal, visual and written communication skills to educate and work with cross functional teams on controlled experiments Experimentation design or A/B testing experience is preferred. Experience in leading a team required.

Job Title – Data Scientist (Forecasting)

Anicca Data is seeking a Data Scientist (Forecasting) who is motivated to apply his/her/their skill set to solve complex and challenging problems. The focus of the role will center around applying deep learning models to real-world applications.  The candidate should have experience in training, testing deep learning architectures.  This candidate is expected to work on existing codebases or write an optimized codebase at Anicca Data. The ideal addition to our team is self-motivated, highly organized, and a team player who thrives in a fast-paced environment with the ability to learn quickly and work independently.

Job Location: Remote (for time being) and Bangalore, India (post-COVID crisis)

• At least 3+ years of experience in a Data Scientist role
• Bachelor's/Master’s degree in Computer Science, Engineering, Statistics, Mathematics, or similar quantitative discipline. D. will add merit to the application process
• Experience with large data sets, big data, and analytics
• Exposure to statistical modeling, forecasting, and machine learning. Deep theoretical and practical knowledge of deep learning, machine learning, statistics, probability, time series forecasting
• Training Machine Learning (ML) algorithms in areas of forecasting and prediction
• Experience in developing and deploying machine learning solutions in a cloud environment (AWS, Azure, Google Cloud) for production systems
• Research and enhance existing in-house, open-source models, integrate innovative techniques, or create new algorithms to solve complex business problems
• Experience in translating business needs into problem statements, prototypes, and minimum viable products
• Experience managing complex projects including scoping, requirements gathering, resource estimations, sprint planning, and management of internal and external communication and resources
• Write C++ and Python code along with TensorFlow, PyTorch to build and enhance the platform that is used for training ML models

Preferred Experience

• Worked on forecasting projects – both classical and ML models
• Experience with training time series forecasting methods like Moving Average (MA) and Autoregressive Integrated Moving Average (ARIMA) with Neural Networks (NN) models as Feed-forward NN and Nonlinear Autoregressive
• Strong background in forecasting accuracy drivers
• Experience in Advanced Analytics techniques such as regression, classification, and clustering
• Ability to explain complex topics in simple terms, ability to explain use cases and tell stories

 Hiring for Azure Data Engineers.

Location: Bangalore

Employment type: Full-time, permanent

website: www.amazech.com

Qualifications: 

B.E./B.Tech/M.E./M.Tech in Computer Science, Information Technology, Electrical or Electronic with good academic background.

Experience and Required Skill Sets:

•       Minimum 5 years of hands-on experience with Azure Data Lake, Azure Data Factory, SQL Data Warehouse, Azure Blob, Azure Storage Explorer

•       Experience in Data warehouse/analytical systems using Azure Synapse.

Proficient in creating Azure Data Factory pipelines for ETL processing; copy activity, custom Azure development, Synapse, etc.

•       Knowledge of Azure Data Catalog, Event Grid, Service Bus, SQL, and Purview.

•       Good technical knowledge in Microsoft SQL Server BI Suite (ETL, Reporting, Analytics, Dashboards) using SSIS, SSAS, SSRS, Power BI

•       Design and develop batch and real-time streaming of data loads to data warehouse systems

 Other Requirements:

A Bachelor's or Master's degree (Engineering or computer-related degree preferred)

Strong understanding of Software Development Life Cycles including Agile/Scrum

Responsibilities: 

•       Ability to create complex, enterprise-transforming applications that meet and exceed client expectations. 

•       Responsible for the bottom line. Strong project management abilities. Ability to encourage the team to stick to timelines.

TOP 3 SKILLS

Python (Language)

Spark Framework

Spark Streaming

Docker/Jenkins/ Spinakar

AWS

Hive Queries

He/She should be good coder.

Preff: - Airflow

Must have experience: -

Python

Spark framework and streaming

exposure to Machine Learning Lifecycle is mandatory.

Project:

This is searching domain project. Any searching activity which is happening on website this team create the model for the same, they create sorting/scored model for any search. This is done by the data

scientist This team is working more on the streaming side of data, the candidate would work extensively on Spark streaming and there will be a lot of work in Machine Learning.

INTERVIEW INFORMATION

3-4 rounds.

1st round based on data engineering batching experience.

2nd round based on data engineering streaming experience.

3rd round based on ML lifecycle (3rd round can be a techno-functional round based on previous

feedbacks otherwise 4th round will be a functional round if required.

• You're proficient in AI/Machine learning latest technologies  
• You're proficient in GPT-3 based algorithms 
• You have a passion for writing code as well as understanding and crafting the ways systems interact
• You believe in the benefits of agile processes and shipping code often
• You are pragmatic and work to coalesce requirements into reasonable solutions that provide value

• Deploy well-tested, maintainable and scalable software solutions
• Take end-to-end ownership of the technology stack and product 
• Collaborate with other engineers to architect scalable technical solutions
• Embrace and improve our standards and processes to reduce friction and unlock efficiency

Company Overview:

Rakuten, Inc. (TSE's first section: 4755) is the largest ecommerce company in Japan, and third largest eCommerce marketplace company worldwide. Rakuten provides a variety of consumer and business-focused services including e-commerce, e-reading, travel, banking, securities, credit card, e-money, portal and media, online marketing and professional sports. The company is expanding globally and currently has operations throughout Asia, Western Europe, and the Americas. Founded in 1997, Rakuten is headquartered in Tokyo, with over 17,000 employees and partner staff worldwide. Rakuten's 2018 revenues were 1101.48 billions yen. 　 -In Japanese, Rakuten stands for ‘optimism.’ -It means we believe in the future. -It’s an understanding that, with the right mind-set, -we can make the future better by what we do today. Today, our 70+ businesses span e-commerce, digital content, communications and FinTech, bringing the joy of discovery to more than 1.2 billion members across the world.

Website : https://www.rakuten.com/">https://www.rakuten.com/

Crunchbase : https://www.crunchbase.com/organization/rakuten">Rakuten has raised a total of https://www.crunchbase.com/search/funding_rounds/field/organizations/funding_total/rakuten">$42.4M in funding over https://www.crunchbase.com/search/funding_rounds/field/organizations/num_funding_rounds/rakuten">2 rounds

Companysize : 10,001 + Employees

Founded : 1997

Headquarters : Tokyo, Japan

Work location : Bangalore (M.G.Road)

Please find below Job Description.

Role Description – Data Engineer for AN group (Location - India)

Key responsibilities include:

We are looking for engineering candidate in our Autonomous Networking Team. The ideal candidate must have following abilities –

• Hands- on experience in big data computation technologies (at least one and potentially several of the following: Spark and Spark Streaming, Hadoop, Storm, Kafka Streaming, Flink, etc)
• Familiar with other related big data technologies, such as big data storage technologies (e.g., Phoenix/HBase, Redshift, Presto/Athena, Hive, Spark SQL, BigTable, BigQuery, Clickhouse, etc), messaging layer (Kafka, Kinesis, etc), Cloud and container- based deployments (Docker, Kubernetes etc), Scala, Akka, SocketIO, ElasticSearch, RabbitMQ, Redis, Couchbase, JAVA, Go lang.
• Partner with product management and delivery teams to align and prioritize current and future new product development initiatives in support of our business objectives
• Work with cross functional engineering teams including QA, Platform Delivery and DevOps
• Evaluate current state solutions to identify areas to improve standards, simplify, and enhance functionality and/or transition to effective solutions to improve supportability and time to market
• Not afraid of refactoring existing system and guiding the team about same.
• Experience with Event driven Architecture, Complex Event Processing
• Extensive experience building and owning large- scale distributed backend systems.

Job Description for :

Role: Data/Integration Architect

Experience – 8-10 Years

Notice Period: Under 30 days

Key Responsibilities: Designing, Developing frameworks for batch and real time jobs on Talend. Leading migration of these jobs from Mulesoft to Talend, maintaining best practices for the team, conducting code reviews and demos.

Core Skillsets:

Talend Data Fabric - Application, API Integration, Data Integration. Knowledge on Talend Management Cloud, deployment and scheduling of jobs using TMC or Autosys.

Programming Languages - Python/Java
Databases: SQL Server, Other Databases, Hadoop

Should have worked on Agile

Sound communication skills

Should be open to learning new technologies based on business needs on the job

Additional Skills:

Awareness of other data/integration platforms like Mulesoft, Camel

Awareness Hadoop, Snowflake, S3

Role and Responsibilities

• Execute data mining projects, training and deploying models over a typical duration of 2 -12 months.
• The ideal candidate should be able to innovate, analyze the customer requirement, develop a solution in the time box of the project plan, execute and deploy the solution.
• Integrate the data mining projects embedded data mining applications in the FogHorn platform (on Docker or Android).

Core Qualifications
Candidates must meet ALL of the following qualifications:

• Have analyzed, trained and deployed at least three data mining models in the past. If the candidate did not directly deploy their own models, they will have worked with others who have put their models into production. The models should have been validated as robust over at least an initial time period.
• Three years of industry work experience, developing data mining models which were deployed and used.
• Programming experience in Python is core using data mining related libraries like Scikit-Learn. Other relevant Python mining libraries include NumPy, SciPy and Pandas.
• Data mining algorithm experience in at least 3 algorithms across: prediction (statistical regression, neural nets, deep learning, decision trees, SVM, ensembles), clustering (k-means, DBSCAN or other) or Bayesian networks

Bonus Qualifications
Any of the following extra qualifications will make a candidate more competitive:

• Soft Skills
  • Sets expectations, develops project plans and meets expectations.
  • Experience adapting technical dialogue to the right level for the audience (i.e. executives) or specific jargon for a given vertical market and job function.
• Technical skills
  • Commonly, candidates have a MS or Ph.D. in Computer Science, Math, Statistics or an engineering technical discipline. BS candidates with experience are considered.
  • Have managed past models in production over their full life cycle until model replacement is needed. Have developed automated model refreshing on newer data. Have developed frameworks for model automation as a prototype for product.
  • Training or experience in Deep Learning, such as TensorFlow, Keras, convolutional neural networks (CNN) or Long Short Term Memory (LSTM) neural network architectures. If you don’t have deep learning experience, we will train you on the job.
  • Shrinking deep learning models, optimizing to speed up execution time of scoring or inference.
  • OpenCV or other image processing tools or libraries
  • Cloud computing: Google Cloud, Amazon AWS or Microsoft Azure. We have integration with Google Cloud and are working on other integrations.
  • Decision trees like XGBoost or Random Forests is helpful.
  • Complex Event Processing (CEP) or other streaming data as a data source for data mining analysis
  • Time series algorithms from ARIMA to LSTM to Digital Signal Processing (DSP).
  • Bayesian Networks (BN), a.k.a. Bayesian Belief Networks (BBN) or Graphical Belief Networks (GBN)
  • Experience with PMML is of interest (see www.DMG.org).
• Vertical experience in Industrial Internet of Things (IoT) applications:
  • Energy: Oil and Gas, Wind Turbines
  • Manufacturing: Motors, chemical processes, tools, automotive
  • Smart Cities: Elevators, cameras on population or cars, power grid
  • Transportation: Cars, truck fleets, trains

About FogHorn Systems
FogHorn is a leading developer of “edge intelligence” software for industrial and commercial IoT application solutions. FogHorn’s Lightning software platform brings the power of advanced analytics and machine learning to the on-premise edge environment enabling a new class of applications for advanced monitoring and diagnostics, machine performance optimization, proactive maintenance and operational intelligence use cases. FogHorn’s technology is ideally suited for OEMs, systems integrators and end customers in manufacturing, power and water, oil and gas, renewable energy, mining, transportation, healthcare, retail, as well as Smart Grid, Smart City, Smart Building and connected vehicle applications.

Press:  https://www.foghorn.io/press-room/">https://www.foghorn.io/press-room/

Awards: https://www.foghorn.io/awards-and-recognition/">https://www.foghorn.io/awards-and-recognition/

• 2019 Edge Computing Company of the Year – Compass Intelligence
• 2019 Internet of Things 50: 10 Coolest Industrial IoT Companies – CRN
• 2018 IoT Planforms Leadership Award & Edge Computing Excellence – IoT Evolution World Magazine
• 2018 10 Hot IoT Startups to Watch – Network World. (Gartner estimated 20 billion connected things in use worldwide by 2020)
• 2018 Winner in Artificial Intelligence and Machine Learning – Globe Awards
• 2018 Ten Edge Computing Vendors to Watch – ZDNet & 451 Research
• 2018 The 10 Most Innovative AI Solution Providers – Insights Success
• 2018 The AI 100 – CB Insights
• 2017 Cool Vendor in IoT Edge Computing – Gartner
• 2017 20 Most Promising AI Service Providers – CIO Review

Our Series A round was for $15 million.  Our Series B round was for $30 million October 2017.  Investors include: Saudi Aramco Energy Ventures, Intel Capital, GE, Dell, Bosch, Honeywell and The Hive.

About the Data Science Solutions team
In 2018, our Data Science Solutions team grew from 4 to 9.  We are growing again from 11. We work on revenue generating projects for clients, such as predictive maintenance, time to failure, manufacturing defects.  About half of our projects have been related to vision recognition or deep learning. We are not only working on consulting projects but developing vertical solution applications that run on our Lightning platform, with embedded data mining.

Our data scientists like our team because:

• We care about “best practices”
• Have a direct impact on the company’s revenue
• Give or receive mentoring as part of the collaborative process
• Questions and challenging the status quo with data is safe
• Intellectual curiosity balanced with humility
• Present papers or projects in our “Thought Leadership” meeting series, to support continuous learning