Despite the impactful recession, job profiles like Data Scientist and Analyst have witnessed an exponential growth in various organisations. According to a recent study, amid the lockdown, specific domains and technologies across the IT space continue to develop at a steady pace. This has called for jobs like data analytics, AI, machine learning, deep learning, among others.
In this article, we list the six latest Data Science and Analysts jobs openings one can apply now.
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(The list is in no particular order)
1| Data Scientist at Accenture
About: As a Data Scientist, your responsibilities will include developing analytics-based solutions which will produce quantitative as well as qualitative business insights. You will work with the partners to integrate systems and data quickly and effectively.
For this job, you will need to have experience in data science frameworks, Jupyter notebook, AWS Sagemaker. You will be expected to have adequate experience in data mining techniques like regression, random forest, boosting, text mining, social network analysis and more.
2| Imaging Data Scientist (AI Applications) at Intel
About: As an Imaging Data Scientist (AI Applications) in Intel’s Computational Imaging Technology (CIT) group, you’ll be developing new computational tools and AI applications, using your knowledge and creativity to solve hard and real problems at the intersection of process and design.
You will be actively engaged in developing new algorithms, working to invent new methods, and applying cutting edge software methods and tools. It requires 3+ years of work or educational experience in demonstrated coding proficiency and background in computational geometry or geometry algorithms related to CAD tool development.
3| Analyst, Analytics & Metrics at Mastercard
Location: Pune, Gurgaon
About: As a Data Analyst, you will be focussing on supporting Go-To-Market and Sales Enablement leveraging data analytics to enable data-driven sales and decision making across all C&I products, services and processes. You will analyse large volumes of transaction and product data to generate insights and actionable recommendations to drive business growth, apply knowledge of metrics, measurements, and benchmarking to complex and demanding solutions, among others.
You need to have a good understanding of data mining, model development, time series analysis, forecasting, Hadoop, Python, R, MS-Excel and PowerPoint skills and create highly predictive models using segmentation and regression techniques to drive profits.
4| Data Scientist at Bottomline Technologies
About: As a member of the data and analytics team, you will be developing software for a range of ML and data mining techniques. This will include techniques like predictive modelling, customer profiling and segmentation, recommendations, text analytics, and big data analytics, among others.
The candidate is required to have at least two years of professional experience in major programming languages such as Java, Python and Scala.
5| Data Scientist – Delivery at Uniphore
About: As a Data Scientist at Uniphore, you will be expected to identify anomalies and apply data to propose solutions for adequate decision making in the conversational automation space across various business verticals like finance, health, etc. You will be building ML algorithms and design experiments to merge, manage, interrogate and extract data to supply tailored reports to customers or broader organisations.
You will also use ML and statistical techniques to provide solutions to problems such as extracting insights to improve agent performance in driving sales efficacy and more. You are expected to have 5-6 years of hands-on experience in building statistical models and more than four years of experience in advanced analytics/predictive modelling in a consulting role.
6| Data Analyst at Infinx
About: As a Data Analyst, your responsibilities will include interpreting data, analyse results using statistical methods as well as provide ongoing reports, develop and implement databases, acquire data from primary or secondary data sources and more.