Role Description:
The Spec Analytics Intermediate Analyst is a developing professional role,
reporting to AVP/VP leading the team. Deals with most problems independently
and has some latitude to solve complex problems. Integrates in-depth
specialty area knowledge with a solid understanding of industry standards
and practices. Applies analytical thinking and knowledge of data analysis
tools and methodologies. Requires attention to detail when making judgments
and recommendations based on the analysis of factual information. Typically
deals with variable issues with potentially broader business impact. Applies
professional judgment when interpreting data and results. Breaks down
information in a systematic and communicable manner. Developed communication
and diplomacy skills are required to exchange potentially complex/sensitive
information. Moderate but direct impact through close contact with the
businesses' core activities. Quality and timeliness of service provided will
affect the effectiveness of own team and other closely related teams.
Few notables among the multiple areas that we work in –
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Drive Digital Marketing, Product Sales & Engagement:
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Optimizing Digital Servicing Channels (Website & Mobile App):
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Leverage Advanced Analytics and AI enhance customer interactions,
particularly in areas like Chatbot performance and personalized user
experiences.
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Lead the industrialization and enhancement of our "Test & Learn"
capability, enabling the rapid design, execution, and measurement of
experiments for new digital features and marketing campaigns
Responsibilities
:
-
Interpret complex data sets to identify significant trends, patterns,
and anomalies, translating these into clear, concise, and impactful
insights that support informed decision-making for business partners and
senior leadership.
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Identifies and compiles data sets using a variety of tools (e.g. SQL,
Python, PySpark) to help predict, improve, and measure the success of
key business to business outcomes
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Utilize statistical methods and analytical tools to extract meaningful
insights from large and complex datasets.
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Responsible for documenting data requirements, data collection /
processing / cleaning, and exploratory data analysis, which may include
utilizing statistical models / algorithms and data visualization
techniques
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Incumbents in this role may often be referred to as Data Scientists
Technical Skills:
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Hands-on Experience in Python, SQL & Machine Learning (ML) is a
must. Experience with PySpark is preferred.
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Writing clean, efficient, and well-documented code according to design
specifications and coding standards.
-
Knowledge of digital marketing and Credit Card business, and industry
best practices is highly beneficial.
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Experience working and collaborating with multiple stakeholders.
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Ability to guide and mentor the junior team members. Ability to build
partnerships with cross-functional teams.
Qualifications:
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Bachelor’s or Master’s Degree with at least 5 years of working
experience
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Ability to identify, clearly articulate and solve complex business
problems and present them to the management in a structured and simpler
form
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Hands-on experience working with large, complex, unstructured dataset,
data warehouses and ability to pull data using relevant programs and
coding
-
Experience in working on Investment Analytics, Retail Analytics, Credit
Cards, Services, Banking & Markets Financial Services be nice to
have
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Excellent communication and interpersonal skills, be organized, detail
oriented, flexible, and adaptive to matrix work environment
Education
:
-
Bachelors/University degree or equivalent experience
This job description provides a high-level review of the types of work
performed. Other job-related duties may be assigned as required.
Additional Job Description
-
Experience in Python, PySpark, Hive, Impala, SQL programing will be
preferred
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Credit card Business and P&L experience would be preferred
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Knowledge on Adobe, Test & Learn and another web analytics tool.