Role of a Data Scientist

A data scientist is someone who:

  • Better at statistics than any other software engineer.
  • A  Data Scientist is unlike an Analyst creates data.
  • Scientist who has access to more measurements (data) than ever before
  • Converting raw data into pictorial or statistical reports.
  • Then sending reports to the higher level for analysis/predictive and calculative analysis.
  • A mix of multiple positions: Data intake, Visualization, Model Creation, Analysis, Data Operations etc
  • Develop methodologies and execute on them to expand knowledge.

Skill Sets:

  • Good at analyzing and ability to communicate findings to both business and IT leaders in an influence way.
  • Strong business acumen
  • Inquisitive in nature

 

 

Desired Candidate

  • Technically Sound – R, SAS, python, java, hive/pig/SQL.
  • Data scientists have to be well versed in regression.
  • Hands clear on probability, time series, and linear algebra.
  • Computer science and applications, modeling, statistics, analytics.
  • Search engines
  • Social networks
  • IT/Software
  • Financial institutions
  • The health care
  • Engineering companies Oil industry
  • Retail
  • Telecom/Mobile analytics
  • Marketing agencies
  • Data science vendors
  • Environment, utilities government and defense
  • Manufacturing

 

Salary Range:

Minimum INR 5 LAC

 

Role of a Data Analyst

What is the Role of Data Analyst?

The Role of Data Analyst comprises of the following task, a data analyst is a person who:

  • Perform a variety of tasks related to collecting, studying, and organizing, comparing and interpreting statistical information and provide appropriate solutions.
  • Data tracking and identifying the trends and patterns in the marketplace are very important tools.
  • Intense research work..
  • Search and evaluate the information related to the particular requirements of a client.
  • Audit the report, and present it an appealing manner to the client.
  • Data mining, data mapping and data warehousing.

Skill Sets:

  • You also need to be well versed in Excel, SQL, SAS, VB, SPSS, Swindon or Gloucester, Micro Strategy.
  • Strong verbal and writing skills, along with presentation skills.
  • Knowledge in specialized data management software
  • Strong problem solving skills.
  • Proficiency with data compilation and analysis.

Employers View/ Educational Qualification:

  • Every industry has a need for data analysis, at least at certain level.
  • Most employers require data analysts to hold at least a degree preferably in statistics, IT, Engineering, or similar technology or other coursework may be acceptable.
  •  Substantial related field experience is also acceptable.

Industries Hiring Data Analyst:

  • Search engines
  • Social networks
  • IT/Software
  • Financial institutions
  • The health care
  • Engineering companies Oil industry
  • Retail
  • Telecom/Mobile analytics
  • Marketing agencies
  • Data science vendors
  • Environment, utilities government and defense
  • Manufacturing

 

Salary Range:

MEDIAN: Rs 299,024

Demanding Future:

Data analysts have high growth prospects.

If you have the required qualifications and skills, and are keenly interested in pursuing a career in this field, then being a data analyst is a good option for you.

If lagging behind in terms of qualification then enroll now! The opportunity to learn and gain the skills required for Data Analyst.

Career Opportunities in Business Analytics Segment

Opportunities in Business Analytics

The use of Business Analytics is now not limited to only specifically Information Technology function/ Industry but widespread across all industries and functions namely E-commerce, Healthcare, Banking and Insurance, Biotechnology, Pharmaceutical, Fraud Management, Human Resource Management, Logistic-Inventory Management etc. Wide range of career opportunities in business analytics. In turn this has led to a tremendous pick to a number of jobs in the similar segments having a Business Analysis expertise. This has brought those who are in search of jobs into segments other then boring IT roles in advantage.

12 Growing career opportunities in business analytics
Below are the list of a few Analytic roles across industries:

Business Analytics Future Market Prospects

As per the research conducted on Business Analytics Future Market Prospects it has been found out that more than 50% of the new analytics jobs in the business analytics industry will be in India. The use of business analytics is spreading fast, bringing enormous benefits to companies in industries from natural resources to electronic media. But when it comes to analytics talent—people with the ability to use statistics, quantitative analysis and information-modeling techniques to make business decisions—a critical mismatch between supply and demand is looming.

Since 2012 there has been an impressive increase in the demand for Analytics professionals and Data Scientists. The lure of excellent job prospects within the analytics sector saw a rise in the number of students and professionals eager to gain analytic skills. The corporate world as well took big strides integrating analytics within all layers of their business. India was seen to be the preferred outsourcing destination for IT and ITeS services reason being a highly talented workforce, lower costs and operational efficiencies among others was the reason for this.

Companies will need innovative skills and sourcing strategies to secure the talent they will need. In numerous nations, organizations can no more depend on colleges to give a pipeline of individuals with strong math and statistics skills. As per research, many developing countries are turning out more prominent quantities of graduates with degrees in quantitative fields, delivering an increasing number of the world’s analytics talent.

Analytics is moving from an optional part in business to the center of numerous key choices and techniques. In a late overview of 258 North American business pioneers led by Accenture Analytics and SAS, 72 percent of respondents said they would increase spending on business analytics in 2012 in excess of 2011 levels.

Analytical tools that integrate Hadoop and R,
gained popularity, especially with small and mid-size organizations. Leading Hadoop distribution vendors Cloudera with revenue growing to $61   and MapR with $23 million enjoyed significant revenue growth in 2012.

The growing significance of analytics is most evident in the commercial enterprises that have constantly depended on that discipline, for example analytics. Banks, for instance, are employing more risk managers to guide new-product development in a manner that does not endanger FICO scores. Insurers progressively depend on statisticians and speculation modelers as well as on analysts who can help the organization enhance client and customer acquisition their maintenance and retention.

Likewise at the cutting edge of this pattern are businesses where analytics has as of late turned into a vital capacity. Energy organizations, for instance, used to contract experts predominantly for determining supply and interest. Presently they depend on them to discover new wellsprings of oil and characteristic gas, to support the productivity of boring projects and to enhance such courses of action as workforce arranging and equipment maintenance.

Indeed segments where analytics is still in its outset remember it as critical for future development. Organizations in the electronics and cutting edge industry, for instance, are avid for individuals who can help the whole association understand rising client and customer segments and enhance marketing efforts.

In addition, the burgeoning demand for analytics capabilities means that many companies will not be able to meet their needs solely with in-house talent. This means that more and more advanced analytics work will be sourced externally from companies in the growing business analytics services industry.

Likewise, the thriving demand for analytics abilities implies that numerous organizations won’t have the capacity to address their needs singularly with in-house talent. This implies that more developed analytics work will be sourced remotely from organizations in the developing business analytics services industry.

As per the research the business analytics services industry will include 30,500 of those new jobs, more than any of alternate commercial enterprises as per the research. Despite the fact that this $50-billion or more industry has to a great extent been focused in the United States and Western Europe, it is quick extending to the rest of the world. More than 50% of the new analytics jobs in the business analytics industry will be in India. Regardless the fact that the United States will make about 39,000 of the new analytics jobs amid that period, India, China and Brazil are all developing their analytics work-forces at a faster cut. At the current rate, in just over 10 years, India and China will utilize almost 50% of every last one of analytics talent in the commercial ventures considered.

Please see the graph below:

Where the jobs are

The United States has the most analytics jobs. However, they are being created in China, India and Brazil at a faster pace.

One of the studies says – Sector to grow to $1.15 billion by 2015.

  • During an era when analytics is getting to be more pervasive, helping organizations (businesses) crosswise over divisions, India is relied upon to keep up its edge over major offshore goals, for example, China, the Philippines, Eastern Europe and Latin America, as indicated by a late report.
  • The demand for this service from India will be determined by an assemblage of components, for example, accessibility of talent pool, development of the business and a wide range of services, says a report arranged by financial services firm Avendus Capital.
  • Data analytics is the technique for utilizing raw information by far reaching utilization of statistical and quantitative analysis with the end goal of drawing business-related conclusions and for foreseeing business results. The banking and financial segments, one of the most punctual adopters of information services, are the biggest client of analytics, emulated by the retail, health insurance and pharmaceutical areas.

 

India at to be spreading wings in Analytics Services
Estimated offshore knowledge services in India by 2015
  • 39% Business research as percentage of market
  • $5.6 billion Total market opportunities
  • 23% Legal process outsourcing as percentage of market
  • 21% Data analytics services as percentage of market
  • 17% Others (Social media research, marketing & sales support, procurement services)
Acquisitions by Indian companies in analytics space

 

Date Acquirer Target Acquisition
size ($ mn)
 Mar ‘07  WNS Mark tics Technologies, an
offshore analytics services
provider
65
Oct ‘07 Cognizant MarketRx, a US-based
analytics solutions provider
135
 Sept ‘11 Genpact US-based Symphony
Marketing Solutions
43
 Sept ‘11 Genpact EmPower Research, a research
& media monitoring company
NA
 Apr ‘12  Wipro Promax Application Group, an
Australian analytics firm
36.5

 

Analytics in Media & Entertainment

[cs_column column_size=”1/2″][cs_image column_size=”1/1″ image_style=”plain” cs_image_url=”http://www.datapanaceaonline.com/wp-content/uploads/2014/10/gemservices.jpg” cs_image_url1=”Browse”][/cs_image][/cs_column][cs_column column_size=”1/2″]Now is perhaps the most exciting and challenging times yet for marketers. Exciting, because the advent of social media has made it easier, quicker and vastly economical for companies to pitch to a wide range of audience. Social media has democratized advertising and marketing in ways that we thought were not possible a few years back. It is less about deep pockets and more about creativity and targeted marketing. At the same time it is challenging because it begs the questions – how do you maximize and measure the efficacy of the campaigns, ensure that the product is pitched to the intended audience and most importantly how do you better a competitor’s campaigns?

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Specifically with respect to the media and entertainment industry, there was a time when marketing and advertising of films meant ensuring every inch of hoarding space in the city is filled with the posters of the upcoming movie and of course the mandatory promotion party or unveiling of the film. More often than not, the success of a film was a function of the popularity of the lead cast since the plots more or less followed a set formula that we are all too well aware of. The early 90’s saw the change that came to define the entire media and entertainment industry. This was the period when liberalization gave Indian viewers exposure to international media content. A new market emerged from this period of immense churn.

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A generation of viewers were born, who had completely different tastes and preferences, a generation born in the era of the World Wide Web. Marketers and film makers came to realize that the dynamics of film making and viewership has evolved. Independent and niche films that never saw the light of the day earlier are now appreciated and is common place, thriving alongside mainstream cinema. Although this new age movies were made, their marketing budgets could not compete with that of commercial cinema and it was not feasible to mass market due to the inherent quality of the cinema itself. It became a cause of concern for the movie makers that the niche movies they made never received the recognition and viewership it deserves simply because they could not reach out to the target audience efficiently enough. They did have access to the social media and realized soon enough that it was their ally, but the answer to how to leverage it into a potent marketing aid eluded them.

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Along comes data analytics to solve this conundrum. Data analytics helped movie makers to generate the “buzz” required to promote a film by harnessing the immense power of big data to provided insights into viewer behavior. Data scientists strategized and optimized the method of reaching out to potential viewers in a precise and highly efficient manner. It is interesting to know the kind of solutions that big data comes up with to aid in marketing. They scour the internet and social media to arrive at answers to questions such as – what time of the day am I likely to generate the highest response for my marketing pitch, what day of the week will it generate the highest level of interest, who is most likely to re-tweet or further share my pitch, based on past patterns or (likes and dislikes) of which user can I say that he/she is most likely to watch this movie or buy this product, do they have friends with similar interest? Data analytics asks such pertinent questions and more often than not arrives at the answers to them by churning through huge volumes of data generated over the internet.

A recent case study by IIM Bangalore that analyses the impact of digital media marketing and the box office collections of a film highlights the role and use of data analytics as a differentiating factor in a highly competitive media and entertainment industry. The study was conducted on the success of the movie “1920 – Evil Returns” – a low-budget horror movie released in 2012. It was especially crucial for targeted marketing of this movie owing to the niche content of the film – horror. They ensured a high level of engagement with the potential viewers through Facebook updates, YouTube videos, sponsored advertisements the whole gamut of social marketing tools at their disposal. The film eventually did open to success due to the precise and sustained marketing campaign run by the movie makers with the assistance of data scientists. It is evident now that the media and entertainment industry has taken note of the power of analytics to drive data analytics and we won’t be surprised to see further interesting marketing techniques unraveled by the magic of big data and analytics.

ROMI Analysis

[cs_column column_size=”1/2″][cs_image column_size=”1/1″ image_style=”plain” cs_image_url=”http://www.datapanaceaonline.com/wp-content/uploads/2014/09/ROMI.jpg” cs_image_url1=”Browse”][/cs_image][/cs_column][cs_column column_size=”1/2″]Students often ask me after doing MBA in marketing how BA program going to help them. Finance & marketing are two pillars of any business. Understanding customer behavioral pattern, predicting sales and devising marketing & online strategy is one of the focus areas in any BA program.  This kind of programs will help you, increasing sales and reducing marketing cost by doing customer segmentation and creating promotional activities.

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Case-let to explain the concept:

ABC Inc. client engagement Group is every now and again captivated; to help customers see how their showcasing exertions effect lead generation and sales. These solicitations come in numerous shapes and sizes yet have a tendency to coalesce around:

  • Which media are “moving the needle” and at what spending levels?
  • How do the different media work together?
  • How can I improve targeting for my direct marketing efforts?

The first two questions are typically answered through what we call a Return on Marketing Investment (ROMI) analysis.  The second question focuses on understanding customer behavioral pattern, predicting sales and devising marketing & online strategy.

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The Solutions:

What is a ROMI Analysis?

A Return on Marketing Investment (ROMI) analysis is fairly a new matrix, helps organizations understand the effectiveness of their marketing spending.  A ROMI analysis examines business results in relation to specific marketing activity. Online marketing becoming the primary source of lead generation and sales it got to be even more critical to analyze and streamline their expense. The benefit of this knowledge is that it allows marketers to focus their spending on activities that provide the greatest return.

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When would you use a ROMI Analysis?

The findings of ROMI analyses can help determine:

  • Which marketing activities are generating substantial leads and which are redundant? E.g. single page flyers are not doing well now a days)
  • Which are marketing areas providing substantial revenue at the same time required high level spending. Which required funds to be reallocated? E.g. for Warner bros.  a particular movie required more funds in Europe than Asia for promotional activities.
  • Which external market conditions (e.g. spending capacity of customer varies from city to city ) affect marketing’s ability to generate results?  How does competitive activity impact the required level of marketing investment
  • How should incremental funds be allocated?

A ROMI analysis, using statistical analysis / data mining tools and techniques, can uncover patterns about how and when customers purchase. This data might be exceptionally profitable in predicting sales and formulating relevant marketing strategies.

How Return on Marketing Investment (ROMI) is Different from Return on investment (ROI)

Return on marketing investment (ROMI) is the contribution attributable to marketing (net of marketing spending), divided by the marketing ‘invested’ or risked. It is not like the other ‘return-on-investment’ metrics because marketing is not the same kind of investment.

ROI vs ROMI

Return on investment (ROI) is a measure of the profit earned from each investment. It’s typically expressed as a percentage, so multiply your result by 100. In simple terms, the calculation is:

(Return – Investment) x 100 = _ %
Investment

 

ROMI

ROI calculations for marketing campaigns (Return On Marketing Investment) can be complex — you may have many variables on both the profit (return) side and the investment (cost) side.The tricky part is determining what constitutes your “return,” and what is your true investment. For example, different marketers might consider the following for return:

 

  • Total revenue generated for a campaign (the top line sales generated from the campaign)
  • Gross profit, or a gross profit estimate, which is revenue minus the cost of goods to produce/deliver a product or service. Many organizations simply use the company’s COG percentage (30%) and deduct it from the total revenue.
  • Net profit, which is gross profit minus expenses.

On the investment side, it’s easy for marketers to input the media costs as the investment. Other costs incurred to execute your campaign you should include:

  • Creative costs
  • Distribution costs (such as PAYG email credits)
  • Printing costs
  • Technical costs (such as email platforms, website coding, hosting etc)
  • Management time
  • Cost of sales

 

3 Common & Proven ROMI Formulas:

 

  • Use gross profit for units sold in the campaign and the marketing investment for the campaign
  • Gross Profit – Marketing/Investment Marketing Investment
  • Use Customer Lifetime Value (CLV) instead of Gross Profit. CLV is a measure of the profit generated by a single customer or set of customers over their lifetime with your company
  • Customer Lifetime Value – Marketing Investment/ Marketing Investment
  • Profit – Marketing Investment – *Overhead Allocation – *Incremental Expenses/Marketing Investment

How Analytics Can Transform the U.S. Retail Banking Sector

[cs_column column_size=”1/2″][cs_image column_size=”1/1″ image_style=”plain” cs_image_url=”http://www.datapanaceaonline.com/wp-content/uploads/2014/09/facturas.jpg” cs_image_url1=”Browse”][/cs_image][/cs_column][cs_column column_size=”1/2″]No matter how you slice it, banking is a data heavy industry. But despite the proliferation of data, effective mining of insights has remained elusive. Given the tremendous advances in analytics software and the processing power generated by cloud-based utility computing architectures, the banking industry is ripe for change.[/cs_column] As the industry works its way out of the financial crisis (amid continued uncertainty over the future), retail banks, in particular, must seriously consider using analytics to improve decision-making, uncover unseen innovation opportunities and improve compliance within a more stringent regulatory environment that is emerging through the Dodd-Frank Act and other impending mandates.

 

These regulations place a high priority on transparency and are pushing banks toward enterprise wide data architectures. This will command a significant (and much-needed) move away from the

siloed approach to computing that has defined banking since the dawn of the digital age, toward a more integrated model in which a single version of the truth is needed to drive business effectiveness and efficiency.

 

Such an approach will power the industry’s push to reinvigorate its relationship with customers. In today’s rapidly changing competitive landscape, regaining customer trust is a top priority for banks as they look to boost revenues and profitability to survive and thrive in uncertain times.

 

[cs_column column_size=”1/2″][rev_slider blog-image][/cs_column][cs_column column_size=”1/2″]Following the economic crisis of 2007–2008, consumers have become more frugal. The age of conspicuous consumption has been replaced by needs-based pragmatic purchasing, a transformation

that pundits interpret as a return to traditional American values. The personal savings rate, which had decreased dramatically in the 1990s, is now showing a small but steady rise.

 

Despite shrinking discretionary spending budgets, consumers (especially those in the millennial demographic) have eagerly adopted new technology, especially smart phones. They have also embraced social networks in big numbers, replacing, in some cases, expensive physical world interactions with a free social variant.

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Their rapidly evolving behavior and preferences cannot be ignored. For banks looking to boost their top lines, these channels offer a simple and powerful way to spread their gospel and build tighter relationships with customers.

 

At the center of this ongoing change is pervasive data — information that banks have possessed all

along but never quite figured out how to exploit. Given that the quality and quantity of data varies

greatly, banks need to prioritize the unique information they hold to accelerate time to insight.

 

By applying new analytical tools and service delivery methods, banks can more quickly convert data into

knowledge to acquire market and service-differentiating capabilities. Such an effort requires the backing

of the organization’s leaders and a cultural shift toward evidence-based decision making.

 

New regulations require banks to provide data that is predictive and risk based. This will require deployment of analytical tools on data aggregated from various business units. Reaching customers effectively via new channels and enhancing the multichannel banking experience will require continuous analysis of the structured customer data residing inside traditional databases and the unstructured bits of data created by customers via mobile phones and social media.

 

In our view, the winners in this unfolding scenario will be those financial institutions that realize the

value of their data and capitalize on it by employing advanced analytics. We believe that banks

should seek to achieve the following through their

Analytics deployment:

  • Predict future scenarios and enhance compliance.
  • Gain insights into what makes them unique and put this insight to use to gain a competitive edge.
  • Drive a customer-centric strategy and improve customer-focused activities.
  • Improve decision-making.
  • Enhance process efficiencies and operating margins by analyzing data to identify inefficiencies.
  • Leverage the emerging analytics-as-a-service model to better manage risk and tap three key resources: people, processes and infrastructure, bundled together to serve as a utility.

Ref: cognizant reports | august 2011