Data science is a rapidly expanding profession with numerous intriguing job prospects for anyone with the necessary skills and expertise. There are numerous possibilities available to you whether you are just starting out in your profession or seeking a change. In this article, we'll highlight the top 10 data science jobs of the week, so you can see what's available and find the perfect opportunity for you.
The candidate should assist in the management of large-scale data science initiatives that make use of data transformation and machine learning models. To design first-rate tools and insights for leadership, and balance the complexity of data, coding/visualization platforms, and client demands. Increase efficiencies and scalability by automating and streamlining tasks.
Responsibilities -To ensure that efforts are focused on providing significant and practical outcomes, apply critical thinking and issue statement definition, deconstruction, and problem-solving. Adopt and create data engineering approaches such as data source and feature identification and integration, data pipelining, feature engineering, data munging, and analysis using script/code-driven methods that can be translated from research to production.
The Customer Remediation Analytics team is searching for new team members to help with analytics tasks such as customer remediation population identification, remediation execution, exploratory analytics, and transactional testing. As a team member, you will be responsible for supporting customer remediation analytics execution activities and pre-execution transactional testing.
Roles and responsibilities – Adopt and create data engineering approaches such as data source and feature identification and integration, data pipelining, feature engineering, data munging, and analysis using script/code-driven methods that can be translated from research to production. Using proper mathematical methods, natural language processing (NLP), and semantic analysis, analyse and create explanatory, predictive, and prescriptive models.
The skill set of an ML Engineer: A candidate with Python/PySpark experience is required, as is experienced in constructing and maintaining data/ML pipelines using AWS Sagemaker. Experience in building ML models using Sagemaker is required, as is experienced with AWS Personalize and AWS EventBridge.
They are searching for a motivated Data Scientist to join their expanding team. The new hire will be responsible for collaborating with other data scientists and engineers across the firm to develop production-quality models for a wide range of Razorpay problems.
The candidate's role and responsibilities include performing complex data analysis to gain insight from massive data stores, collaborating with cross-functional groups such as engineering, sales, and policy to increase automation, updating policies, fixing product vulnerabilities, and providing a secure online experience for users.
The following abilities are required of the candidate: Programming languages include Python, R, SQL, ML methods, ML for Responsible AI, AI domains such as NLP, voice, computer vision, structured data, and learning patterns such as supervised, unsupervised, and reinforcement learning. Tools for data analysis, machine learning, model deployment and scalability Dataset knowledge, pre-built models available in the open community, and third-party providers.
Responsibilities – Ability to understand a problem description and independently execute analytical solutions and methodologies with independent/proactively/thought leadership. Collaborate with stakeholders across the organisation to find opportunities for using company/client data to create business solutions. Create high-quality solutions and insightful analyses by conceptualising, designing, and delivering them.
The individual would work on cutting-edge problems for the bank as part of the asset analytics and data science team. The individual will collaborate closely with stakeholders from risk, business, partnerships, and digital strategies to develop and refine campaign tactics to boost the bank's profitability and growth.
Overall, these are just some of the many data science job openings available this week.
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