Analyst Career Guide

If you want to progress firstly in  this professional then you must develop qualities like passion for numbers, eye for details and team player. A software engineering course with a strong knowledge and idea of data mining, processing and familiarity with SQL or the software (SAS, SPSS,  SQL Server, Oracle, Teradata, Clementine )  is the must. Within a year or two you will be accelerating in your career as an Analytics from Fresher – Experienced Analyst –  Managerial Roles – Head Analytics – AVP- Business Leader. Really Analytics is a very interesting and challenging profession with excellent compensation.

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What is Analytics

Analytics can be defined as the extensive use of data for statistical and quantitative analysis, explanatory and predictive modeling and fact-based decision making. Analytics closely resembles statistical analysis  and data mining, but tends to be based on solving a specific business problem by gathering relevant data and information and analyzing it to take an informed business decision.


Analytics is one of the sunrise careers of not just the Indian digital economy but also the global economy. While careers in data mining and analytics have typically been offered by the business process outsourcing sector under the sub-brand of knowledge process outsourcing, increasingly robust demand for analytics professionals has come from information technology firms, banks, telecom companies and other sector in India.

Why is it needed ?
Analyst jobs, Research Analyst Jobs, Credit Analyst Jobs, Financial Analyst Jobs, Data Analyst Jobs

Firstly, the data that is generated by most organization is bulky and unstructured. This data has to be mined to extract the relevant information. This is an opportunity for ‘data miners’. Here, you need a smart IT professional to work with software and Excel sheets to bring this data into a readable format. Once the data has been generated it requires quantitative skills to analyze and give actionable steps for the organization. For instance, whether it is the banking industry, insurance, telecom or retail, they do have volumes of data on customers, their transactions, personal details but all of this has to be analyzed by smart minds to give a more engaged customers experience and to increase repeat sales volumes.

The outsourcing industry has made Indian a destination for more specialized analytics-based services, enabling global organisations to make enduring decisions. This could involve simple solutions such as keeping organisation in touch with the alerts and signals produced by their respectable industries as they go through their life cycle. This involves generating valuable information on how the industry is changing, growing, consolidating and keeping an eye on the competition. This helps you, the analyst, to identify and response to major chances within your macro environment.


With more people and business going online everyday, web analytics is poised to become one of the hottest career trends of the next give to 10 years (Gartner). More metrics will be used to measure the effectiveness of an e_business in terns of operation, customer experience and return on investment; web data analyst help enterprises priorities web channel activities and solutions.

The scope for Analytics

NASSCOM as one of the six hottest tech sectors expected to grow significantly in the next few years. While there have been widely varying estimates from different industry research organisation on the current size and growth rates of this market, independent research suggest that about 4000 professionals are employed in various analytics services businesses in India and this talent pool is rapidly growing at about 40 % annually. The key limitations of these estimates is that there isn’t an industry standard definition for what  constitutes “analytics services”, which is a subset of what is now commonly termed the  knowledge services or the knowledge process outsourcing (KPO) services industry. In recent years these jobs are with several specialist service providers and global third-party services providers as well as captive centres that have set up analytics services teams to feed such growing market demand.

Key Drives of growth


The key driver of growth is the fact that any industry and any company would require this service. Whether they build this skill set-in-house or outsource it to a vendor, in the future this service would be required in a big way. However, various industry research organisation have opined that enterprises are more likely to source knowledge services from their in house or captive centres, rather than outsourcing such activities to third party service providers. The reason for this include the business sensitivity of data, inherent intellectual property protection issues  and the need to build and maintain such organizational skills and capabilities in-house for sustained competitive advantage.

Whether in-house or outsourced, the industry has to acquire talented or build over time to meet the growing demand. In India, due to the increase in outsourcing and software industries, data mining has become an important segment of technical works. To the world, India is well known as the back office. Apart from customer care and tech support, many outsourcing companies are venturing into data mining with the increase in demand from overseas. The analytics services industry thus presents the opportunity for India to transcend  the realm of labor arbitrage into high value professional services with higher revenue and margin realization. Five years ago, the volume of outsourced work to India sent a great deal of fairly low-end work over here. Today, however, the quality of work being outsourced to India has improved, and we can expect more high-value work to come in.

Source: Analytics Services in India : A Talent Perspective, Dec 2008, Careernet Research Publication.

Types of data Analytic

Reporting or Descriptive Analytics:

As organisation go about their business, they gather a lot of information on sales, volumes, prices at the distributor level, retailer level and about competition. This information helps them to get a sense of the current health of business and possible future trends.

Modeling, or Predictive Analytics:
Predictive Analytics refers to the art and science of analyzing and finding patterns in data to build-up predictive recommendations. These recommendation can range from which type of customer to call by phone for a credit card or insurance, to which type of mobile scheme to offer to a cell phone customer by SMS, or to which kind of customer are likely to default on the loans they have taken. Extensive use of econometrics and statistics is undertaken.

Data-driven strategy:

This is also called test control or champion-challenger testing. This is done by segmenting the date population into test (on which a new strategy called the challenge strategy is to be tested) and control (which uses an existing strategy called champion strategy). Building association rules which describe which parts of the product or customer data are clustered or co-related together are also part of analytics.

Basic domains with in Analytics

Data-driven analytics, by definition, thrives is industries which have large amounts of data and high-volume transaction, and which need systematic and scientific analytics to cut costs and grow sales. The following domains offer employment opportunities to both newcomers and experienced Analytics professional. These can be both in domestic firms, captive outsourcing firms, or third-party business process outsourcing companies.

Retail sales Analytics

Retail sales Retailers require analytics on outlet level data on uptake of particular items, inventory buildup, etc. All this helps them to improve their supply chain as well as sales. For example, a retailer found that sales of chocolates and Chiclets increased when they were taken out from the food counter and kept next to the cash counter. In US, every Walmart store has two dedicated analytics personnel tracking sales, shelf-space,, pricing info and inventory.

Financial services Analytics

Financial services use analytics extensively. This is because they are in a very competitive field, have millions of customers and a lot of transaction. Analytics help them segment customers and make targeted offering. For example, if client data shows a spurt in spending, they also are likely to contact you with a personal loan offer.

  • Risk and credit Analytics
  • Marketing Analytics
  • Collections Analytics
  • Fraud Analytics
  • Pricing Analytics


A growing field in India based on the wealth of information gathered by telecom firms on the calling, SMS and other VAS (value added service) usage habits of customers.

Pharmaceutical or clinical Analytics

Clinical trials depend on the test and control of thousand of patients trying out new drugs. Clinical trial analytics focus on a large number of variables that may or may no affect the drug response.

Pharmaceutical or clinical Analytics

Clinical trials depend on the test and control of thousands of patients trying out new drugs. Clinical trial analytics focuses on a large number of variables that may or may not affect the drug response.

Supply chain Analytics

Supply chain analytics comprises inventory optimization, tracking turn-around time, multiple reports, and how to minimize the distribution costs.

Transportation Analytics

Transportation analytics, while covered more extensively in the field of operations research, seeks to minimize route length, fuel cots or fare pricing

Online or website Analytics

Website analytics focus on analyzing traffic to the website and how to retain visitors on the website for a longer time or encourage them to purchase more goods. It also involves a bit of search engine optimization to make sure the website is high up in the results provided by search engine.

What is your career path as an Analytics?

(Analyst jobs, Research Analyst Jobs, Credit Analyst Jobs, Financial Analyst Jobs, Data Analyst Jobs)

Typically, everyone starts with an analyst role. It starts with analyzing operational data. As the analyst grows in the organisation and gains business acumen, he is then capable of getting into business analytics. The analyst would then have opportunity to become a consultant with firms like McKinsey or Boston Consulting Group.

Career progression in analytics follows the broad pattern as follows:

Fresher :
As an entry-level programmer or analyst, you would be required to write code to generate reports, or clean data to prepare it for analysis. You would also be expected to pick-up nuances of business data, what data is usually wrong, what are the outliers to spot, besides learning the programming language to retrieve and manipulate data. This phase could last for up two years. As you grow, you will also assist in recruiting and training fresher.

Experienced Analyst :
For a period of three to five years of relevant experience, you would then be working as a Senior Analyst / Assistant Manager with official duties in data analysis with some people responsibilities. Depending on your aptitude and organizational abilities, you can tweak the level of business exposure, people management with the amount of technical analysis / skills.

Managerial Roles :
After a period of up to five years, you would be full-time dealing directly with clients, people management, requirements gathering, and translation to technical details for your team. This will also involve recruiting, mentoring junior members and technical training.

Head ( Analytics) / Associate Vice President / Business Leaders :
You can expect to be a business leader within eight to ten years of full experience. The focus will be to grow your team size, maximize customer satisfaction, and deliver innovative analytics that positively impact business revenues.

Why did I choose this career?

It happened! I did not plan to get into this career but it was the first job I took. However, I can tell you the reasons that have made me stick to it.

  • Scope of learning : This career poses a new scope to learn every day. Different clients have different set of queries to be answered. This gives a new perspective and unmatched knowledge exposure.
  • Exercising the mind : I know my mind still works. Working with numbers gives me a high. It lets the mind draw inferences on different situations and come up with smart answers.
  • Creativity : This career has allowed me to use my creativity to unleash the power of numbers that is hidden in the volumes of data given to us.
  • Culture: The culture of the organisation is professional and healthy.

What are the required skill sets?

The most important skills required to work in this job are as follows:

  • Logical and analytical thinking : I was not from a statistics background but have been able to do well because of my logical thinking.
  • Eye of detail : Data Analytics is about putting the smallest pieces together to get the big picture. It is very important to have an eye for detail. You can’t afford to go wrong, you have to be 100 percent accurate and that can only come from analyzing to minute details.
  • Work in teams : For every project, you have to work in a team and deliver the solution for a client. You have to look a the bigger picture and work towards that goal for the benefit of the organisation.

What about the Mind Set?

It’s no a lazy man’s job! It requires lots of hard works, sense of numbers and technical capabilities. Knowledge of package such as SAS and SPSS is helpful in this career. Business acumen as a min set is critical to the profession; one need to know the over all business environment of the client, economic scenario and how they should make their decisions.

Attributes needed for the job include statistical skills. IT-savvy and project management experience. Detail-oriented, excellent analytics skills and the ability to translate and conceptualize statistical information to determine user habits and trends; an understanding of web navigation and user habits; HTML knowledge required, Java and Active Server Page experience come in handy.

Analytics required strong attention to details, quantitative acumen, hard work, and ability to think creatively in terms of how to design test and control for strategy building. An ability to pick up programming languages fast is a must as the large amounts of data is manipulated using software.

Sample Job Description for a Risk Analyst

Summer of Position

Provides analytical and or MIS ( Management Information System) support of various credit policies, risk and/or marketing related functions.

Principal Accountabilities

  • Provide support for analytical research projects and/or statistical models to include project design, data collection, database design, analysis and presentation of results.
  • Conduct cost and profitability studies of customer groups, merchants and/or loan types of business unit operations. Evaluate and implement internal and external credit scoring using traditional and advanced forms of predictive technology.
  • Complete analysis and document results of alternative risk management options and credit risk issues. Design and prepare analyses of operating data; formally present findings to management.
  • Analyze loan and customer credit risk performance using corporate databases Utilize external scoring and/or management software packages to aid in managing account acquisition and portfolio management.
  • May design and/or write technical programs for statistical analysis of portfolio and/or credit bureau performance and monitoring.
  • May prepare exhibits and supporting materials and developing recommendations for credit and pricing policies, credit bureau usage, bulk acquisitions, new load or merchant program structures, profitability/pricing for accounts and portfolios and provide revenue, cost, delinquency and loss forecasts.
  • May assist in establishing, monitoring, evaluating, developing and implementing strategies for new account acquisition, credit limit setting and account management.
  • May ensure account acquisition or account management systems are operating efficiently. May code, test, program and implement new policy changes for account acquisition or account management systems.
  • Adhere strictly to compliance and operational risk controls in accordance with company and regulatory standards, policies and practices; report control weaknesses, compliance breaches and operational loss events.
  • Compete other related duties as assigned and support the company’s diversity programs.

Knowledge, Skills and Abilities

  • This position requires an individual with:
  • One year proven statistical analysis and/or MIS experience, or equivalent. Knowledge and understanding of financial services preferred.
  • Bachelor’s degree in mathematics, statistics, finance, economics, related field or equivalent experience; Master’s degree preferred.
  • Good organizational, analytical, problem-solving and verbal and written communication skills.
  • Proficiency with personal computers as well as pertinent mainframe systems and software packages.

Employers can be either an organisation with a captive analytics unit or a third-party analytics firm.

There are captive analyst divisions, where the analyst works specifically with  a certain vertical. For example with AOL you could work purely on web analytics determining how to increase traffic or conversion rates. In Dell you could be looking at how to optimize inventory. Therefore, you would be specializing in a specific domain.

Third-party analytics firms :
These are firms that are hired by companies for specific projects or for a certain time period. These analysts cut across various industries, thereby gaining a broad range of experience.

What makes people successful in this career

Krishnan Venkata, with Latent View Analytics in Chennai, says that people who get into this field after five to 10 years of experience in a particular business domain have a definite advantage: “When you have an analyst with a pure mathematical and statistical background, very often the strategies turn out to be useless as it is completely devoid of on-ground business reality.”


If you want to change tracks (to get our of analytics) after spending part of your career in it, you would need to learn new skills. The applications to other industries are limited.

What are the alternate mid-career changes that are possible?

Since it is such a young field in India, there are few examples of people making mid-career switches. Very often, analysts take up further studies in order to upgrade their skills. The applications of these skills to another industry all together are limited. Many analysts go on to become consultants.

Krishnan Venkata, an analyst with Latent View says, “It is is never easy to change careers, but there are natural roles in different lines of businesses to which people an transition. For a Sales / BD person, he could move to other high end services/ product selling roles in firms in IT / BPO / Consulting / research, etc. For a delivery person, it would be a harder shift but the natural cross-road is to be a domain expert / consultant. For example, an analyst in financial services analytics could grow to become a domain expert / consultant in the field of financial services.”

Hey says that the transitions people make at the management level are shifts to strategy consulting or account management in similar lines of businesses, such as KPO / BPO / IT services. There have also been people who move into equity research / financial analysis / investment banking. At the analyst level, since some of the skills developed are programming and statistical modeling they could move to a domain or consultant role

Educational / training institutions

In most cases, a software engineering course with a strong knowledge and idea of data mining, processing and familiarity with SQL or associated software (SAS, SPSS, SQL Server, Oracle, Teradata, Clementine) help. But there are a few course available which include data mining.

  • SAS R&D India (Pvt.) Ltd., New Delhi
  • PGDITM Course, National Institute of Industrial Engineering, Mumbai
  • PGPM, Lal Bahadur Shastri Institute of Management, New Delhi

Career growth over time



Pay Growth


Tier-1 schools

Tier-2 Schools

Entry Level

7-8 Lakh

5 Lakh

Mid-level 4 yrs

10 Lakh

8 Lakh

7-8 years

13-15 years

10-12 Lakh

3rd-party firms are paid usually 20 percent less than the captives.

Related Books

  • Web Analytics: An Hour a Day by Avinash Kaushik
  • Competing on Analytics: The New Science of Winning by Thomas H. Davenport and Jeanne G. Harris
  • Google Analytics 2.0 by Jerri Ledford and Mary E. Tyler
  • The Analytic Field: A Clinical Concept (EFPP Series (European Federation for Psychoanalytic Psychotherapy)) by Antonino Ferro and Roberto Basile
  • Web Analytics For Dummies (For Dummies (Computers)) by Pedro Sostre and Jennifer LeClaire
  • The Deciding Factor: The Power of Analytics to Make Every Decision a Winner by Larry E. Rosenberger, John Nash, and Ann Graham
  • Actionable Web Analytics: Using Data to Make Smart Business Decisions by Jason Burby, Shane Atchison, and Jim Sterne
  • Cognitive Analytic Therapy: Developments in Theory and Practice by Anthony Ryle
  • Yahoo! Web Analytics: Tracking, Reporting, and Analyzing for Data-Driven Insights by Dennis R. Mortensen
  • Fundraising Analytics: Using Data to Guide Strategy (The AFP/Wiley Fund Development Series) by Joshua M. Birkholz
  • Systems for Change in Literacy Education: A Guide to Professional Development by Carol A. Lyons and Gay Su Pinnell
  • Analytic Mapping and Geographic Databases (Quantitative Applications in the Social Sciences) by G Garson and Robert S. Biggs
  • SAP xApp Analytics by Ryan Leask and Mathias Pöhling
  • Supporting and Sustaining Teachers’ Professional Development: A Principal’s Guide by Dr. Marilyn Tallerico
  • Epidemiology for Health Promotion and Disease Prevention Professionals by Richard E Miller
  • Advanced Web Metrics with Google Analytics by Brian Clifton
  • Analytic Life: Personal and Professional Aspects of Being a Jungian Analyst by New England Soc of Jungian Analysts
  • Professional Practice 101: Business Strategies and Case Studies in Architecture by Andrew Pressman and Thomas Fisher
  • The Analytic Encounter: Transference and Human Relationship (Studies in Jungian Psychology by Jungian Analysts) by Mario Jacoby
  • The Concept of Analytic Contact: The Kleinian Approach to Reaching the Hard to Reach Patient by Waska
  • Curing Analytic Pathologies: Pathways to Improved Intelligence Analysis by Jeffrey R. Cooper
  • Meta-Analytic Procedures for Social Research (Applied Social Research Methods) by Dr. Robert Rosenthal
  • Preparation For Licensing And Board Certification Examinations in Psychology: The Professional Legal & Ethical Components (Brunner/Mazel Continu) by Robert G. Meyer
  • When Professionals Weep: Emotional and Countertransference Responses in End-of-Life Care (Series in Death, Dying, and Bereavement) by Renee Katz and Therese Johnson
  • Cognitive Analytic Therapy and Later Life: A New Perspective on Old Age by Jason Hepple
  • The New Know: Innovation Powered by Analytics (Wiley and SAS Business Series) by Thornton May
  • Analytic Philosophy: The History of an Illusion (Continuum Studies in Philosophy) by Aaron Preston
  • Applied Equity Analysis: Stock Valuation Techniques for Wall Street Professionals by James English
  • CIW:Internetworking Professional Study Guide Exam 1D0-460 (With CD-ROM) by Patrick T. Lane and Rod Hauser
  • Professional Learning: Gaps and Transitions on the Way from Novice to Expert (Innovation and Change in Professional Education) by Henny P.A. Boshuizen, Rainer Bromme, and Hans Gruber
  • Teaching as a Professional Discipline: A Multi-dimensional Model by Dr Geof Squires
  • Beyond Monopoly: Lawyers, State Crises, and Professional Empowerment by Terence C. Halliday
  • Basic Evaluation Methods: Analysing Performance, Practice and Procedure (Personal and Professional Development) by Glynis M. Breakwell and Lynne Millward
  • A House Divided: Comparing Analytic and Continental Philosophy by C. G. Prad
  • Proven Strategies in Competitive Intelligence: Lessons from the Trenches by John E. Prescott, Stephen H. Miller, and The Society of Competitive Intelligence Professionals
  • Professional Perspectives on Fixed Income Portfolio Management, Volume 1 by Frank J. Fabozzi
  • Professional Resumes for Accounting, Tax, Finance and Law: A Special Gallery of Quality Resumes by Professional Resume Writers by David F. Noble
  • Enactments in the Analytic Situation: A Focused Study of Five Analysts’ Identification andExperience of Enactment and the Role They Played by Robert Gregory Field
  • Strategic Enterprise Management: Tools for the 21st century (Cima Professional Handbook) by Martin Fahy (Paperback – Jan 14, 2002)

Source : Digit Fast Track to Tech Careers: Your Handy Guide to Everyday Technology

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