This report is the fifth annual list of the ‘best firms for data scientists to work for’ published by Analytics India Magazine (AIM).

This report aims to rank firms based on how well suited a company’s policies are for their employees. Last year, AIM expanded the scope by reaching out to a wider set of firms with data science teams in their organisations. In continuation with the initiative, we surveyed hundreds of employers in India to glean insights into how they have created an exemplary work environment for data scientists.

For previous year’s rankings: 2022 | 2021

We derived an overall index to determine the rankings of AIM’s best firms for data scientists to work for. AIM listed five parameters to compute the ranking of 50 firms — Learning & Support, Productivity & Engagement, Benefits & Well-being, Rewarding Excellence and Diversity & Inclusion. The overall index was calculated using the average score of five sub-indices (based on the parameters mentioned above). The sub-indices themselves were calculated based on the scores given to the answers (of the survey questions) asked by AIM. These scores were normalized on a scale from 0 to 1 before the average for the sub-indices was taken. Based on the responses of the participating firms, AIM Research has identified best practices being followed by top performing firms under each sub-index. The best practices for each sub-index have been mentioned under respective sections.

No fee was charged for participation in the survey, and the participation was voluntary.

Below we discuss the results of the analysis and present the top-ranking companies across the different sub-indices and the overall index. We highlight the various policies or initiatives that these companies undertook, for which they were listed in the top 50.

1

Greater Emphasis on Learning Platforms: 100% of top-performing firms already provide access to learning platforms for their employees. Considering this and the rapid pace of technological changes, we can expect an upward trend, with more firms prioritizing continuous learning and development opportunities for their data scientists.

2

Investment in Cutting-Edge Technology: Currently, 57% of top performers are investing in cutting-edge technology, such as high-performance GPUs. As data science becomes more complex and compute-intensive, we can expect an increasing number of firms to invest in advanced infrastructure to support their data scientists.

3

Increasing Focus on Diversity and Inclusion: The report shows 35% of women in senior leadership roles in top-performing firms and a 51% representation of women in data science teams. As diversity and inclusion continue to be a major focus, these numbers are likely to increase in the coming years, fostering more diverse and inclusive workplaces.

4

Emphasis on Peer-to-Peer Recognition: Currently, 40% of top performers have peer-to-peer recognition programs in place. As companies strive to foster a positive work culture and employee engagement, we may see an increase in firms implementing similar recognition initiatives.

5

Promotion of Cross-Functional Collaboration: Currently, 40% of top performers promote cross-functional collaboration. This trend is expected to rise as more firms recognize the benefits of interdisciplinary cooperation and the innovation it can bring.

Rankings 2023

All the firms that submitted responses have formulated workplace policies or undertaken initiatives in an effort to build a conducive work environment and provide all the resources needed for data scientists to be content and successful at their jobs. Some companies did better than others.

Learning & Support

The “Learning and Support” index in the report is a measure of how well a company supports the ongoing professional development and learning of its data scientists. This is a critical aspect of a data science firm as the field of data science is continuously evolving, and professionals in this field need to keep their skills updated to stay competitive.

The index takes into account a variety of factors including:

Access to L?earning Platforms: This includes providing data scientists with access to various online learning platforms such as Coursera, Udemy, DataCamp, and LinkedIn Learning, as well as internal training programs specifically designed for data science.

Mentorship Programs and Leadership Skills: This refers to programs designed to nurture potential leaders within the organisation. These programs may include one-on-one sessions, group sessions, and mentorship by existing leaders.

Buddy Program: This involves programs that help smoothen the onboarding process for new joiners. For example, inviting new joiners for team-building activities even before they formally join the firm to help them integrate into their teams and become productive quickly.

Productivity and Engagement

The “Productivity and Engagement” parameter determines how productive and engaging the data scientists of a firm is. Productivity and engagement of the workforce in general and data scientists in particular is influenced by factors like attrition rate, growth of data science or analytics wing, average tenure of data scientists, etc.

AIM Research has taken into account the following factors that most likely influence the productivity and engagement index. It has identified the optimal scores of each of the factor.

Attrition rate: A healthy attrition rate depends on various factors such as industry, job role, and company culture. However, as a general rule of thumb, an attrition rate of around 10% is considered healthy for companies working in the field of data science.

Growth in analytics/data science: The extent of growth in analytics/data science in the last 12 months depends on various factors such as industry growth, company strategy, and market demand. A growth rate of 60-80% is considered impressive for most companies in the data science industry. However, smaller organizations should eye on growing their data science wings by more than 100% in order to catch up with some of the biggies in the industry.

Benefits and Wellbeing

Employees do not work for remuneration only. They are equally concerned about ancillary benefits and their well-being while being associated with an organization. Thus, it becomes crucial for firms to ensure that employees’ well-being is paid heed to. In contemporary times, organizations have attempted to address this aspect in a more holistic manner as mentioned below.

The index takes into account a variety of factors including:

Comprehensive Leave Policy: Most of the top firms have comprehensive leave policies that include family and parenting leave, sick leave, privilege leave, bereavement leave, long-term leave of absence, and sabbaticals.

Flexible work arrangements: In terms of benefits and well-being, firms providing flexible work arrangements like work from home, flexible working hours, and hybrid work culture stand out and are essentially the top performers in this segment.

Rewarding Excellence

Employees will be motivated to stay with an organization only if they feel they are adequately and justly rewarded for the efforts they have been putting in towards the growth of their organizations. Recognizing this, firms have been coming up with innovative ways to recognize good work that is not limited to quarterly bonuses or yearly promotions.

The index has considered some of the most innovative ways that firms working in the data science domain have taken to reward excellence of employees as mentioned below:

Peer-to-Peer recognition programs: Recognition Programs are at the heart of acknowledging the efforts and achievements of employees. All top performers have recognition programs in place to recognize and differentiate high performers across all segments. These include individual and team awards, tenure awards, spot rewards, etc. Some organizations even have Peer-to-Peer recognition programs where employees can continuously recognize each other’s efforts and achievements fostering a culture of appreciation and recognition within the organization.

Instant Impact Awards: Some firms have also designed Instant Impact Awards that are given immediately on the accomplishment or achievement so that the impact is not lost. This program ensures that employees receive recognition for their efforts in a timely manner.

Diversity and Inclusion

Whether a firm is good from employees’ perspective also depends on how diverse and inclusive the firm is in accommodating people from various backgrounds and providing each of them with equal opportunities to grow and thrive in the organization.

To ensure diversity and inclusion, top-performing companies in the data science domain have been practicing the following conventions.

Employee Network Groups: To promote diversity and inclusion, firms have established Employee Network Groups (ENGs), that provide a safe space for employees with shared characteristics or interests, such as gender, ethnicity, religion, or sexual orientation to discuss and deliberate. ‘Listening tours’ are organized by several firms to gather unfiltered feedback from employees in all areas of the business. Along with promoting diversity, equity and inclusion (DE&I), ENGs provide personal and professional growth opportunities for employees.

DE&I curriculums: Companies have implemented training curriculums related to DE&I such as unconscious bias training, neurodiversity, and managing unconscious bias. They help in raising awareness about biases and promote inclusive behaviours. While conducting talent acquisition drives, firms are required to keep DE&I efforts in mind when conducting any talent acquisition activity. This involves running focused recruitment campaigns, ensuring that the selection panels are diverse and inclusive, and ensuring that the hiring process is free from biases.

Read the full report here:

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