Job Role : AVP Data Sciences
Salary : Rs 36.0 Lakhs to 97.0 Lakhs per year.
Location : Bengaluru, Karnataka
Company : Citi
Qualifications : Bachelor’s degree
Experience : 5-8 years of experience
ABOUT CITI
Citibank, typically known as Citi, is a global monetary organization with a wealthy history relationship lower lower back over 200 years. Established in 1812 due to the fact the City Bank of New York, it has grown into one in all of the maximum crucial banking and financial offerings groups international. Headquartered in New York City, Citi operates in greater than one hundred sixty countries, serving masses of hundreds of customers, collectively with individuals, agencies, governments, and institutions.
Citi offers a large range of monetary products and services, including patron banking, employer and funding banking, securities brokerage, wealth control, and extra. It is thought for its innovation in virtual banking answers and has been on the main fringe of technological advancements in the economic vicinity.
Despite its international presence, Citi has confronted annoying situations over the years, which consist of monetary downturns and regulatory problems. However, it has maintained a sturdy recognition for its dedication to customer support, agency responsibility, and community improvement through diverse responsibilities and partnerships.
Job Description
As AVP of Data Sciences, you may lead strategic tasks in statistics-pushed selection-making, overseeing superior analytics, device mastering models, and statistics governance. You’ll collaborate with cross-purposeful teams to power innovation and insights, leveraging big data technologies and making sure scalable answers. Your role includes handling a group of records scientists, placing KPIs, and enforcing fine practices to optimize information great and integrity. You’ll also contribute to shaping the business enterprise’s facts approach, aligning with commercial enterprise goals, and staying abreast of industry tendencies to maintain aggressive advantage. Success in this role requires robust leadership, technical talent, and a strategic attitude.
Qualifications for a AVP Data Sciences:
- Advanced Degree in Data Science or related discipline: Typically, a Master’s or Ph.D. In Data Science, Computer Science, Statistics, Mathematics, or a associated quantitative subject is required. A strong instructional historical past with a focus on system getting to know, statistical modeling, and facts analysis is critical.
- Proven Leadership Experience: Demonstrated revel in in leading and handling groups of statistics scientists and analysts. This includes placing strategic dreams, dealing with sources effectively, and fostering a collaborative and innovative crew surroundings.
- Expertise in Data Analytics and Machine Learning: Deep understanding and palms-on experience with information analytics tools and strategies, along with statistical analysis, machine learning algorithms, and records visualization. Proficiency in programming languages along with Python, R, or Scala is often required.
- Business Acumen: Ability to translate complicated facts insights into actionable business guidelines. Experience in working intently with stakeholders across exclusive functions to understand commercial enterprise necessities and force data-pushed decision-making.
- Strong Communication Skills: Excellent verbal and written conversation abilities are important for successfully supplying complicated technical statistics to non-technical stakeholders. The potential to steer and convince others based totally on records-pushed insights is also critical.
- Problem-Solving and Analytical Thinking: Strong analytical talents with the ability to analyze massive datasets, identify tendencies, and extract significant insights. Proven capacity to remedy complex problems and make statistics-driven choices.
- Project Management Skills: Experience in managing records technological know-how initiatives from concept to final touch. This includes defining task scope, developing project plans, dealing with timelines and sources, and handing over tasks on time and within budget.(AVP Data Sciences)
- Knowledge of Big Data Technologies: Familiarity with massive records platforms and technologies inclusive of Hadoop, Spark, and SQL databases. Experience in operating with large-scale datasets and optimizing records pipelines for efficiency and scalability.
- Experience in Data Governance and Compliance: Understanding of information governance standards, information privateness regulations (along with GDPR, CCPA), and quality practices for making sure statistics protection and compliance.
Responsibilities for a AVP Data Sciences:
Leadership and Team Management:
- Lead and mentor a crew of data scientists and analysts, providing steering, aid, and professional development possibilities.
- Foster a way of life of innovation, collaboration, and continuous learning in the records technology team.
Data Strategy and Execution:
- Develop and execute a comprehensive records method aligned with commercial enterprise objectives. This consists of figuring out possibilities for leveraging facts to pressure business boom and operational efficiency.
- Partner with senior management and cross-useful groups to define and prioritize statistics science initiatives.
Advanced Analytics and Modeling:
- Oversee the improvement and deployment of advanced analytics and device studying models. This includes carrying out exploratory statistics analysis, characteristic engineering, model choice, and assessment.
- Ensure the accuracy, reliability, and scalability of predictive models and algorithms.(AVP Data Sciences)
Project Management and Execution:
- Manage information technology tasks from initiation to final touch, ensuring alignment with task desires, timelines, and budgets.
- Monitor challenge progress, discover dangers and issues, and put into effect corrective moves as wished.
Cross-Functional Collaboration:
- Work closely with IT, business intelligence, and different departments to integrate records technology answers into existing structures and methods.
- Collaborate with outside partners, vendors, and consultants as needed to support statistics science tasks.
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