Job Title : Sr Advanced Data Scientist
Salary : ₹14,91,965 Per Year.
Location : Bengaluru, Karnataka
Company : Honeywell
Qualifications : Bachelor’s
Experience : 5 to 9 years experience.
ABOUT HONEYWELL
Honeywell International Inc. Is a varied era and production organisation, established in Charlotte, North Carolina, USA. Founded in 1906 by using Mark C. Honeywell, the corporation has grown right into a international powerhouse with a presence in various industries such as aerospace, building technology, overall performance materials, and protection answers.
Honeywell’s aerospace section is a leader in plane engines, avionics, and systems integration. It gives advanced technologies for both business and defense packages. The enterprise’s constructing technologies department makes a speciality of creating green and sustainable environments via its offerings in building automation, strength control, and protection solutions.
Additionally, Honeywell produces a huge range of performance materials and technologies used in diverse industries together with refining, petrochemicals, and automobile. Its safety and productiveness solutions encompass personal protecting gadget, gas detection technology, and productiveness control software program.
Job Overview
A Senior Advanced Data Scientist usually leads complex data evaluation initiatives, making use of superior statistical and predictive modeling strategies to resolve enterprise problems. They excel in decoding facts, growing algorithms, and developing system mastering fashions. Their role includes participating with move-purposeful groups, imparting strategic insights, and supplying findings to stakeholders. They possess robust programming competencies (e.G., Python, R) and talent in gear like SQL and Hadoop. Moreover, they live updated on industry tendencies, make contributions to analyze, and mentor junior team members, using innovation and optimizing choice-making procedures inside the organization.
Role and Responsibilities for a Sr Advanced Data Scientist:
- Data Analysis and Modeling: Utilize advanced statistical techniques and machine getting to know algorithms to investigate massive datasets and derive actionable insights.This includes predictive modeling, clustering, category, and time series analysis.
- Problem Solving: Identify key enterprise troubles and increase analytical answers to deal with them. This entails information commercial enterprise requirements, formulating hypotheses, and validating findings through rigorous testing.
- Algorithm Development: Design and put in force algorithms that beautify facts excellent, automate approaches, and optimize decision-making processes. This can also include developing custom algorithms tailored to specific business wishes.
- Data Visualization and Communication: Present complicated facts-pushed insights to stakeholders in a clean and compelling manner. Use statistics visualization tools (e.G., Tableau, Power BI) to create dashboards and reviews that facilitate understanding and decision-making.
- Collaboration: Work intently with move-practical groups which includes business analysts, engineers, and executives to recognize requirements, prioritize duties, and deliver actionable insights. Collaborate on projects that span a couple of departments or business units.
- Research and Innovation: Stay abreast of enterprise developments and advancements in information technology and machine mastering. Conduct studies, test with new methodologies, and recommend innovative answers to improve enterprise consequences.
- Mentorship and Leadership: Provide steerage and mentorship to junior records scientists and analysts. Lead via instance in adopting excellent practices, selling a data-pushed culture, and fostering expert boom inside the team.(Sr Advanced Data Scientist)
- Project Management: Manage give up-to-end information technology initiatives from inception to deployment. This entails defining challenge scope, setting timelines, allocating sources, and ensuring deliverables meet fine standards.
- Ethical Considerations: Uphold moral standards in records series, evaluation, and utilization. Ensure compliance with records prolateness policies (e.G., GDPR, CCPA) and moral tips in studies and experimentation.
Skills Required for a Sr Advanced Data Scientist:
- Advanced Statistical Analysis: Proficiency in statistical strategies such as regression, speculation testing, and multivariate analysis. Experience with Bayesian strategies and experimental design is a plus.
- Machine Learning: Expertise in supervised and unsupervised gaining knowledge of strategies (e.G., random forests, neural networks, clustering algorithms). Ability to assess version performance and optimize algorithms for scalability and accuracy.
- Programming Languages: Strong programming skills in languages consisting of Python, R, or Java. Experience with libraries and frameworks for facts manipulation (e.G., pandas, numpy) and system mastering (e.G., scikit-analyze, TensorFlow).
- Data Management: Knowledge of database systems (e.G., SQL, NoSQL) and huge statistics technology (e.G., Hadoop, Spark). Ability to deal with big datasets efficiently and extract insights from based and unstructured facts sources.
- Data Visualization: Proficiency in statistics visualization gear (e.G., Tableau, Power BI, matplotlib) to create visual representations of facts styles and traits. Ability to design intuitive dashboards and reviews for numerous audiences.(Sr Advanced Data Scientist)
- Problem-Solving Abilities: Analytical mindset with a knack for identifying styles, outliers, and insights within facts. Experience in growing innovative solutions to hard problems the usage of information-driven methodologies.
- Team Collaboration: Proven capability to paintings correctly in move-useful groups, collaborate with diverse stakeholders, and influence choice-making approaches thru records-pushed insights.
- Adaptability and Learning Agility: Willingness to examine new technology, methodologies, and business domains. Adaptability to evolving challenge requirements and organizational priorities.
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