The domain of Data Science in this data-driven world has started opening a plethora of opportunities with the highest-paid job roles in India— data scientist, data engineer, data analyst, data storyteller, and many more. Since educational institutes have started offering Data Science courses with degrees and certificates, numerous students are getting attracted towards the vast field of Data Science with structured, unstructured, and semi-structured complex datasets. There are innumerable Data Science jobs available in India, especially in tech hubs like Gurgaon and Hyderabad. This article features the vacancy alerts from reputed companies for Data Science jobs in Hyderabad, Telangana.
Oracle Cloud Infrastructure platform is developed for enterprises to help those in higher performance computing with easy migration. There are multiple products and applications available at Oracle— Oracle Cloud Infrastructure, software, hardware, Cloud applications, industry applications, NetSuite, and on-premises applications.
Responsibilities: The data scientists should help in the hands-on development of solutions, demos, and POCs by using Oracle Data Cloud services as well as achieve results through planning, risk management, stakeholder management, conflict resolution, and team management. The candidate needs to exercise creativity, independent judgment, and business acumen through methods and techniques to design non-routine and business solutions with Oracle Data Cloud products. It is essential to influence customer strategy, architecture, and migration planning workshops with relevant expert-level competency across the data ecosystem such as Big Data, advanced analytics, Data Science, and AWS.
Qualifications: The candidate must have more than five years of practical experience in IT, stakeholder management, and two years of domain knowledge of Data Science, Big Data ecosystem, SQL, Python, PySpark, Kafka, NoSQL, etc. It is essential to have experience in enhancing data collection procedures, ad-hoc analysis, creating automated anomaly detection systems, and identifying automation opportunities. The candidate must have strong applied engineering skills, communication skills, and navigating skills.
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Tide is known as the leading provider of UK SME business accounts as well as one of the fastest-growing fintech in the UK. It covers more than 350,000 businesses and aims to transform the business banking market. Tide offers business accounts, banking services, and a comprehensive set of highly connected admin tools for businesses with low fees as well as innovative features.
Responsibilities: The data scientist is expected to split time between statistical analysis, identifying and leveraging new data sources, identifying new applications for Data Science, and learning about different data technologies. The candidate should work closely with business service teams and data engineering teams to deliver business value in an agile framework and build payment classification including data extraction use cases. The data scientist needs to understand business requirements and solutions of data products and identify creative solutions for training datasets. The candidate is required to train models and optimize hyper-parameters.
Qualifications: The candidate must have hands-on experience with Python, R, Julia, Data Science, machine learning libraries, version control, and code repositories. The candidate needs to possess strong analytical skills, mathematical skills, collaboration skills, technical skills, and excellence in an academic background in the field of statistics, mathematics, computer science or economics.
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IBM is an American multinational technology company dedicated to client's success through innovations for the world. It believes in progress that the application of intelligence, reason and science can enhance business, society, and the human condition. It is one of the leading cloud platforms and cognitive solutions companies across 170 countries with over 350,000 employees.
Responsibilities: The data scientist is needed to transform data of clients into tangible business values through analyzing information, communicating outcomes, and collaborating on product development. The candidate should develop, maintain, evaluate, and test Big Data solutions and also help with the design of data solutions with Artificial Intelligence-based technologies such as H2O, TensorFlow, and many more. The candidate needs to design algorithms and implementation such as leading from disparate datasets, pre-processing, and deliver solutions based on high-level architecture. The data scientist also should maintain the production systems such as Kafka, Hadoop, ElasticSearch, etc.
Qualifications: The candidate must have skills in designing algorithms, implementing pipelines, validating model performance, and expertise in IBM Watson services with Python, Spark, SQL, etc. The candidate should have four to six years of experience in the IT industry, two years of experience in real-time Big Data projects, programming languages like Python, Java, NoSQL databases such as MongoDB, HBase, Big Data architectures such as Lambda, Kappa, Oozie, etc, and cluster manager. There should be technology expertise with proven ability in solutions covering data ingestions, data cleansing, data mart creation, and many more.
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Responsibilities: The data engineer needs to be with the Eats Data Solutions team for focusing on optimizing data engineering practices and enhancing Uber Eats data quality. The team creates efficient tools and processes to help people working on data, designs and maintains a holistic view of Eats' data infrastructure resources. The data engineer should focus on providing supports to Uber Eats business by owning top-tier Eats canonical datasets, and building the data platform to allow easy and flexible access to Eats data. The candidate needs to work on both batching and streaming data processing to empower different use-cases.
Qualifications: The candidate is required to have excellent skills in modeling complicated business logic in data, Big Data technologies, and hands-on experience in streaming data processing engines with good communication skills.
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Salesforce is popular for being the world no.1 CRM integrated platform and an American cloud-based software company. It provides CRM services with customer service, marketing automation, analytics, and application development for small businesses and industries such as financial services, manufacturing, education, retail, and media.
Responsibilities: The senior data scientist should work closely with a team of data scientists, data and visualization engineers, analysts, strategists, and many more to create high-visibility data products and decision-making tools for Salesforce leaders. The candidate needs to work on forecasting important business metrics like sales and capacity, churn and propensity modeling, clustering as well as classification with data. The senior data scientist can build end-to-end data for Data Science products by developing, maintaining, and productionalizing new and existing models and algorithms. The candidate is required to build machine learning pipelines to acquire, prepare, and analyze volumes of internal Salesforce data and derive actionable product insights with development strategies.
Qualifications: The candidate needs to have more than six years of industry experience in finding creative solutions to real-world problems with business context, statistics, and machine learning techniques. The candidate should have a strong understanding of machine learning methods, machine learning project lifecycle, model performance monitoring, data transformation, and analytics functions. It is essential to have good communication skills as well as writing skills.
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