You Don’t Necessarily Need A Resume To Get A Data Science Job, Says This H2O.ai Data Scientist
Receiving a data science job offer is getting increasingly difficult as more or less every applicant has the same skills. Consequently, aspirants fail to differentiate themselves from others, thereby diminishing the chances of receiving a job they desire. Apart from just the technical skills, data science aspirants and professionals need to plan effectively for increasing their likelihood of getting selected. However, applicants fizzle out due to the dearth of guidance. Therefore, Analytics India Magazine brings you the journey of a successful data scientist for assimilating their approach and spreading their perspective. For this edition of our weekly column My Journey In Data Science, we got in touch with Parul Pandey, a data science evangelist at H2O.ai. How It All Began Parul has graduated as an Electrical & Electronics Engineering from NIT Hamirpur in 2009. However, she mentioned that enrolling in one of the premier engineering institutes was essential than the stream. Post her graduation she worked as an Analyst in the planning department, where she was introduced to unveiling insights into the power distribution network in Delhi. “I have always been fascinated with numbers, but my real tryst with data science occurred in my first job,” adds Parul. There she learnt to investigate data and perform predictive analysis with SQL, which got her hooked into nuances of data science and machine learning. Preparation Strategy The data scientists first dabbled with C in her undergraduate and later after moving out from here the first job she started learning R and Python from various e-learning platforms such as Coursera and Edx. When asked about the approach, Parul said that she had devised a plan and followed it diligently to ensure compliance. Firstly, she was determined to complete the course before jumping on to another, and secondly, tried to implement the learning at her work. “Sometimes I was able to implement and solve the problem successfully and at times I couldn’t, but in the course, I learned a lot,” explains Parul. In this ever-changing data science landscape, preparing is never straightforward as many developments happen every day. And it wasn’t any different for Parul either. However, her ability to focus on one problem at a time enabled her in learning quickly. Parul’s Unique Job Strategy Unlike others, Parul didn’t directly apply for jobs. Her modus operandi of engaging in building a robust portfolio by adorning GitHub profile, writing on LinkedIn, Medium, and other publications like Towards Data Science, KDNuggets, and Datacamp, has helped her in getting a voice and visibility. Talking about the effectiveness of her strategy, she mentioned that she got the job offer at H2O.ai without even providing a resume. Parul believes that, in the future, resumes will go obsolete, communicating through writing on various platforms is crucial to demonstrate skills. “My first data science experience was very positive, and it was based on what I had accomplished in data science space,” clarifies Parul. “My presence in LinkedIn and Medium gave me a headstart since the recruiters knew me beforehand, the kind of projects I had executed, and what I was capable of.” Continuing on the job strategy, applicants shouldn’t lose self-esteem on getting rejected from employers and continue to improve on their skills for receiving a job offer they desire. Staying Relevant In Data Science Marketplace Over the years, data science has only evolved and became more competitive. Therefore, one needs to enhance their skills to stay relevant in the landscape. “Every day numerous libraries with algorithms afloat in the data science space, thereby, causing imposter syndrome,” acknowledges Parul. “However, as a workaround, she said one has to accept that no one can master all the skills in data science. Thus, we should determine our interest and ability and keep enhancing it.” Although Parul believes in improving her strengths, she didn’t downplay the idea of learning new things. The data scientist said, updating and reskilling is the mantra to remain relevant in the domain. Owing to this, she leverages Kaggle to learn new algorithms and machine learning strategies. Parul’s Data Science Achievements Parul became the LinkedIn Top Voice in the software development category due to her data science evangelism skills. She is one of the most popular influencers who contributes to the data science community through writing and sharing learning resources. Besides, she won an award in the 2019 Kaggle ML & DS challenge, where she analysed women’s representation in machine learning and data science. Determined to support other women in the data science, she has started the Hyderabad chapter of ‘Women In Machine Learning and Data Science’ (WiMLDS), where she encourages women to learn cutting-edge technologies and guides them to make a career switch. “A huge effort is still required in getting more women in the data science field, but things are improving, and we need to keep the momentum going,” says Parul. “It will also require a collaborative effort from society to make diversity and inclusion a vital part of the ecosystem.” Moving forward, Parul is committed to contributing and building an ecosystem for researchers in machine learning and artificial intelligence domain. With the hope of delivering such platforms, she is trying to collaborate with corporates and educational institutions. Advice To Aspirants Data science, in itself, is a great tool to solve real-world problems. Therefore, Parul says that aspirants and data science professionals should keep obtaining new skills and carry out meaningful projects. “While gaining technical skills is paramount, writing is the most underrated skill in data science. However, one should utilise their wiring skills to ensure that they are demonstrating their capability to the community,” concludes Parul.
Receiving a data science job offer is getting increasingly difficult as more or less every applicant has the same skills. Consequently, aspirants fail to differentiate themselves from others, thereby diminishing the chances of receiving a job they desire. Apart from just the technical skills, data science aspirants and professionals need to plan effectively for increasing […]
Data science techniques are one of the most in-demand skills required for organisations. However, aspirants need to differenciate to get a job
["Data Science", "data science job", "H2O AI", "Interviews and Discussions"]
["data science", "artificial intelligence", "machine learning", "AI", "data science job", "ML", "H2O AI", "RAG", "Python", "analytics", "SQL", "Data Science", "R", "Interviews and Discussions"]
["AI", "artificial intelligence", "machine learning", "ML", "data science", "analytics", "RAG", "Python", "R", "SQL"]
Rohit is a technology journalist and technophile who likes to communicate the latest trends around cutting-edge technologies in a way that is straightforward to assimilate. In a nutshell, he is deciphering technology.
Email: rohit.yadav@analyticsindiamag.com