3 Visualization Technologies Jobs

As a Senior Data Scientist, you will apply your expertise in statistics, machine learning, and data analysis to extract valuable insights from structured and unstructured data. You will work closely with cross-functional teams to develop predictive models, improve business processes, and contribute to data-driven decision-making across the organization. Required Skills (Must have) Tech: Advanced programming knowledge in Python and SQL. Advanced knowledge in Probability and Statistics, including hypothesis testing. Advanced knowledge in Practical Machine Learning and awareness of the key-pitfalls in the practice of machine learning and approaches to addressing them. Advanced knowledge of data visualization technologies like Tableau, and PowerBI, and comfortable using relevant libraries in Python like seaborn and matplotlib. Experienced in modern development tools and writing code collaboratively. Intermediate knowledge of Cloud technologies and experience in developing data science solutions in one or more cloud platforms. Experienced in modern development tools, writing code collaboratively and developing solutions on cloud platforms. Non Tech : Ability to recognize and pursue pragmatic alternatives vis--vis a perfect solution, balancing priorities of time with potential business impact. Plan projects, break them down across individual data scientists in the team, track their performance and manage risks. Ability to storyboard an entire presentation to a non-technical audience. Ability to work independently to develop data science solutions, while also being able to work as part of a team to communicate findings and collaborate on solutions. Strong written skills. This is required for submitting technical papers, whitepapers, and developing project documentations. Technical leadership and mentorship to the community of data scientists in the organization. Required Skills (Good to have) Tech: Advanced knowledge in one or more areas besides Machine Learning – Operations Research, Natural Language Processing, Deep learning and its applications, Time Series forecasting at scale. Reinforcement Learning, Graph Machine Learning, Explainable Machine learning. Advanced understanding of Cloud technologies and experience of deploying applications on cloud. Non Tech: Ability to solution critical business problems into its component parts and match each such part with an appropriate technical approach. Roles and Responsibilities As Senior Data Scientist, you will be responsible for a wide range of engagements listed below: Formulates complex problems into hypotheses and proofs of concept for testing. Socializes this with the rest of the team and guides them to deliver on it. Applies business acumen in analyses to extract meaningful and actionable information. Communicates complex ideas and insights effectively to stakeholders with various levels of technical experience. Leverages various analytical techniques, appropriate to solving the business problem at hand. Performs research for solutions and solves problems efficiently to overcome data analytics challenges. Engages in the collection, integration, analysis, and presentation of data for various business contexts Understands good software development practices (versioning, peer reviews, refactoring, and pair programming), adapts them to the needs of the team and sets an example for others by following them. Creates and maintains technical documentation of the scientific experimentations performed, preferably in the CRISP-DM framework or like. Keeps up with the latest trends, technologies, and best practices in the field of Data Science and Engineering. Shares this knowledge with the rest of the data science team. Does peer reviews of codes and approaches of fellow members of the data science team. Provides mentorship to junior data scientists in the team. Looks for improvements in data science delivery processes, actively seeks buy-in on the improvements from peers and managers, implements them in the team and monitors their adoption. 4 to 6 years experience is mandatory

-Design, conceptualize prepare presentations and schematic planning -Coordinating and working along with Sr. interior designers -3D and 2D design development -Material selections, mood board presentations and client meetings -Site supervision

Role & responsibilities As a Data Scientist, you will play a crucial role in analyzing complex data using statistical and machine learning models, providing valuable insights, and driving data-driven decision-making processes Analyze complex data using statistical and machine learning models to derive actionable insights Utilize Python for data analysis, visualization, and working with APIs, Linux OS, databases, big data technologies, and cloud services Develop innovative solutions for natural language processing and generative modeling tasks using NLP, Generative AI, and LLMs Collaborate with cross-functional teams to understand business requirements and translate them into data science solutions Work in an Agile framework, participating in sprint planning, daily stand-ups, and retrospectives Collaborate with cross-functional teams to understand business needs and translate them into analytical solutions. Research, develop and analyze computer vision algorithms in areas related to object detection, tracking, product identification and verification, scene understanding Ensure model robustness, model generalization, accuracy, testability, and efficiency Write product or system development code Design and maintain data pipelines and workflows within Azure Databricks for optimal performance and scalability. Communicate findings and insights effectively to stakeholders reports and visualizations. Preferred candidate profile A Master's degree in Data Science, Statistics, Computer Science, or a related field. Over 5 years of proven experience in developing machine learning models, particularly for time series data within a financial context. Advanced programming skills in Python or R, with extensive experience in libraries such as Pandas, NumPy, and Scikit-learn. Comprehensive knowledge of AI and LLM technologies, with a track record of developing applications and models. Proficiency in data visualization tools, such as Tableau, Power BI, or similar platforms. Exceptional analytical and problem-solving abilities, coupled with meticulous attention to detail. Superior communication skills, enabling the clear and concise presentation of complex findings. Extensive experience in Azure Databricks for data processing, model training, and deployment. Proficiency with Azure Data Lake and Azure SQL Database for data storage and management. Experience with Azure Machine Learning for model deployment and monitoring. In-depth understanding of Azure services and tools for data integration and orchestration.