Job Role: Data Scientist II
Salary: 22,52.040 per year,
Location: Bengaluru, Karnataka
Company: Uber
Qualifications: Bachelor’s degree
Experience : 4+ years experience
ABOUT UBER
Uber Technologies, Inc., primarily based in 2009 via Garrett Camp and Travis Kalanick, is a worldwide generation organization founded in San Francisco, California. Initially known for its adventure-hailing app, Uber has extended its offerings to encompass Uber Eats for food shipping, Uber Freight for logistics, and Uber Advanced Technologies Group for self-riding automobile development. The employer operates in over 900 metropolitan areas in the course of more than 69 nations.
Uber’s platform connects riders with drivers through its app, providing more than a few transportation options, along with favored rides, carpooling, and comfort automobiles. The organization’s goals are to redefine metropolis mobility and decorate accessibility at the same time as addressing environmental and regulatory challenges. Uber’s improvements in the era and its numerous service services have made it a great participant in the global transportation and logistics markets.
Job Description
As a Data Scientist II, you may examine complicated datasets to derive actionable insights and pressure strategic choice-making. Responsibilities encompass growing and implementing superior statistical models and machine mastering algorithms, performing statistics preprocessing and function engineering, and visualizing results to speak findings effectively. Collaborate with bypass-practical groups to end up privy to enterprise desires and translate them into records-pushed answers. Utilize gear that incorporates Python, R, SQL, and records visualization platforms. A sturdy history in information, programming, and statistics manipulation is crucial, together with the capacity to paint independently and manage more than one task.
Responsibilities Of a Data Scientist II:
- Data Analysis and Interpretation: Analyze big and complicated datasets to extract actionable insights and support strategic choice-making. Utilize statistical strategies and system-studying algorithms to model and interpret facts.
- Model Development: Design, increase, and implement advanced statistical models and gadget learning algorithms to resolve enterprise troubles and decorate desire-making tactics. Continuously refine fashions to enhance accuracy and overall performance.
- Data Preparation: Perform data preprocessing, consisting of cleansing, transformation, and characteristic engineering, to ensure statistics are satisfactory and suitable for evaluation.
- Visualization and Reporting: Create clear and compelling facts visualizations to speak findings and insights to both technical and non-technical stakeholders. Develop complete reports and displays to summarize analytical outcomes.
- Cross-functional Collaboration: Work closely with other corporations which include product, engineering, and advertising and advertising and marketing to apprehend their statistics needs and offer information-pushed answers. Translate industrial business enterprise requirements into analytical duties and supply actionable guidelines.( Data Scientist II)
- Tool Utilization: Leverage statistics evaluation and visualization equipment, collectively with Python, R, SQL, and numerous information visualization systems, to carry out duties correctly and efficaciously.
- Continuous Learning: Stay updated with the modern upgrades in records technological understanding, device gaining knowledge of, and statistical methodologies. Apply new techniques and systems to decorate analytical abilties and enhance results.
- Project Management: Manage a couple of tasks concurrently, ensuring well-timed shipping of insights and solutions. Prioritize obligations efficaciously and adapt to converting commercial organization goals.
- Documentation: Document methodologies, strategies, and effects to maintain transparency and reproducibility of analyses. Ensure that documentation is obvious and on hand to unique team people.
Skills Of a Data Scientist II:
- Statistical Analysis: Proficiency in statistical evaluation and strategies, such as speculation sorting out, regression evaluation, and opportunity precept.
- Programming: Strong programming talents in languages collectively with Python or R for record manipulation, version improvement, and evaluation. Experience with libraries in conjunction with Pandas, NumPy, Scikit-research, or similar.
- Data Management: Expertise in SQL for querying databases and handling huge datasets. Familiarity with statistics warehousing and ETL methods.
- Machine Learning: Knowledge of system studying algorithms and techniques, including supervised and unsupervised gaining knowledge of, kind, clustering, and neural networks.
- Data Visualization: Skills in growing effective records visualizations and the usage of equipment which includes Tableau, Power BI, or matplotlib to present complex data in a comprehensible way.( Data Scientist II)
- Problem-Solving: Strong analytical and hassle-solving capabilities, with the ability to approach complicated problems methodically and expand modern answers.
- Communication: Excellent written and verbal communique abilties, with the capability to convey technical data to non-technical stakeholders actually and correctly.
- Attention to Detail: High hobby to element to make certain accuracy in information evaluation, model development, and reporting.
- Teamwork: Ability to collaborate efficiently with pass-useful groups and control stakeholder expectancies.
- Adaptability: Ability to quickly research new gear and strategies, and adapt to evolving commercial enterprise necessities and technologies.
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