Data Engineer

• Partners with business stakeholders to translate business objectives into clearly defined analytical projects.
• Identify opportunities for text analytics and NLP to enhance the core product platform, select the best machine learning techniques for the specific business problem and then build the models that solve the problem.
• Own the end-end process, from recognizing the problem to implementing the solution.
• Define the variables and their inter-relationships and extract the data from our data repositories, leveraging infrastructure including Cloud computing solutions and relational database environments.
• Build predictive models that are accurate and robust and that help our customers to utilize the core platform to the maximum extent.

• 12 to 15 yrs of experience.
• An advanced degree in predictive analytics, machine learning, artificial intelligence; or a degree in programming and significant experience with text analytics/NLP. He shall have a strong background in machine learning (unsupervised and supervised techniques). In particular, excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, logistic regression, MLPs, RNNs, etc.
• Experience with text mining, parsing, and classification using state-of-the-art techniques.
• Experience with information retrieval, Natural Language Processing, Natural Language
• Understanding and Neural Language Modeling.
• Ability to evaluate the quality of ML models and to define the right performance metrics for models in accordance with the requirements of the core platform.
• Experience in the Python data science ecosystem: Pandas, NumPy, SciPy, sci-kit-learn, NLTK, Gensim, etc.
• Excellent verbal and written communication skills, particularly possessing the ability to share technical results and recommendations to both technical and non-technical audiences.
• Ability to perform high-level work both independently and collaboratively as a project member or leader on multiple projects.

Job Title: SQL Query Writer - Analytics Automation

Location: Thane (West), Mumbai

Experience: 4-5 years

Responsibilities:

• Develop and optimize SQL queries for efficient data retrieval and analysis.
• Automate analytics processes using platforms like SQL, Python, ACL, Alteryx, Analyzer, Excel Macros, and Access Query.
• Collaborate with cross-functional teams to understand analytical requirements and provide effective solutions.
• Ensure data accuracy, integrity, and security in automated processes.
• Troubleshoot and resolve issues related to analytics automation.

Qualifications:

• Minimum 3 years of experience in SQL query writing and analytics automation.
• Proficiency in SQL, Python, ACL, Alteryx, Analyzer, Excel Macros, and Access Query.
• Strong analytical skills and attention to detail.

Roles and Responsibilities:

• Design, develop, and maintain the end-to-end MLOps infrastructure from the ground up, leveraging open-source systems across the entire MLOps landscape.
• Creating pipelines for data ingestion, data transformation, building, testing, and deploying machine learning models, as well as monitoring and maintaining the performance of these models in production.
• Managing the MLOps stack, including version control systems, continuous integration and deployment tools, containerization, orchestration, and monitoring systems.
• Ensure that the MLOps stack is scalable, reliable, and secure.

Skills Required:

• 3-6 years of MLOps experience
• Preferably worked in the startup ecosystem

Primary Skills:

• Experience with E2E MLOps systems like ClearML, Kubeflow, MLFlow etc.
• Technical expertise in MLOps: Should have a deep understanding of the MLOps landscape and be able to leverage open-source systems to build scalable, reliable, and secure MLOps infrastructure.
• Programming skills: Proficient in at least one programming language, such as Python, and have experience with data science libraries, such as TensorFlow, PyTorch, or Scikit-learn.
• DevOps experience: Should have experience with DevOps tools and practices, such as Git, Docker, Kubernetes, and Jenkins.

Secondary Skills:

• Version Control Systems (VCS) tools like Git and Subversion
• Containerization technologies like Docker and Kubernetes
• Cloud Platforms like AWS, Azure, and Google Cloud Platform
• Data Preparation and Management tools like Apache Spark, Apache Hadoop, and SQL databases like PostgreSQL and MySQL
• Machine Learning Frameworks like TensorFlow, PyTorch, and Scikit-learn
• Monitoring and Logging tools like Prometheus, Grafana, and Elasticsearch
• Continuous Integration and Continuous Deployment (CI/CD) tools like Jenkins, GitLab CI, and CircleCI
• Explain ability and Interpretability tools like LIME and SHAP

Responsibilities:

• Design and develop strong analytics system and predictive models
• Managing a team of data scientists, machine learning engineers, and big data specialists
• Identify valuable data sources and automate data collection processes
• Undertake pre-processing of structured and unstructured data
• Analyze large amounts of information to discover trends and patterns
• Build predictive models and machine-learning algorithms
• Combine models through ensemble modeling
• Present information using data visualization techniques
• Propose solutions and strategies to business challenges
• Collaborate with engineering and product development teams

Requirements:

• Proven experience as a seasoned Data Scientist
• Good Experience in data mining processes
• Understanding of machine learning and Knowledge of operations research is a value addition
• Strong understanding and experience in R, SQL, and Python; Knowledge base with Scala, Java, or C++ is an asset
• Experience using business intelligence tools (e. g. Tableau) and data frameworks (e. g. Hadoop)
• Strong math skills (e. g. statistics, algebra)
• Problem-solving aptitude
• Excellent communication and presentation skills
• Experience in Natural Language Processing (NLP)
• Strong competitive coding skills
• BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or other quantitative field is preferred

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.

• Collaborating with a team of like-minded and experienced engineers for Tier 1 customers, you will focus on data engineering on large complex data projects. Your work will have an impact on platforms that handle crores of customers and millions of transactions daily.

• As an engineer, you will use the latest cloud services to design and develop reusable core components and frameworks to modernise data integrations in a cloud first world and own those integrations end to end working closely with business units. You will design and build for efficiency, reliability, security and scalability. As a consultant, you will help drive a data engineering culture and advocate best practices.

Job Description