Hello everyone ,Currently devin is in discussion everywhere. People are afraid that this is end of the human software engineering era.<br>Is it really the case ?

No,Devin (AI software engineer) is not definitely going to snatch away software engineer jobs.<br><br>

On their documentation page itself they have mentioned that if the other state of art models were able to perform 5 assisted tasks out of 100 , 2 unassisteed tasks out of 100 , devin.ai software engineer will be able to perform 14 unassisted tasks out of 100. 

It is primarily built on GPT architecture , in a simple words it is a super enhancement of Chat GPT for programmers.

Real software engineering / data science work is way beyond just writing the codes. 

I believe there are 2 components of any project

1. Business execution (Understanding requirement , defining scope , interpreting output ,translating that into business KPI (profit, losses ,costs ,ROI))

Perhaps technical execution will be taken care by AI upto a large extent but translating buisness requirement to machine and interpreting its output is not something which AI can do at this point of time.

Human intelligence cant be adopted by machine as our world requires customized attention to be given for any business problem. There is no standard problem , neither a definite solution. We require to be tangible while working on business requirements.

But ,need of basic programming execution will be surely eliminated as AI will replace human programmers there.

Also there will be few sectors which will be highly impacted because of this.

But if you really understand and are able to add value beyond technical execution to your business then believe me this wont be a threat for you !

This blog talks a about devenai , the first AI software engineer which is in talks a lot these days. This is an attempt to clarify the confusion regarding devind ai.

Devin (AI software engineer) is here to snatch away your job ,Really ?

1. Developed a solution to target customers proactively before they run out of detergent with the help of ML algorithms ,Utilized Survival regressions for calculating repurchases and employed panel regression for feature interpretability through hypothesis testing.
2. Worked on optical character recognition (OCR) for text extraction from product template images.
3. Implemented sentiment classification for client product reviews using advanced models like BERT and various embeddings. Performed topic modeling (LDA, BERT) on the review corpus to identify important topics from liked and disliked reviews.
4. Developed household propensity models using a multi-touch attribution method, utilizing Bayesian regression, odds analysis, and profiling households based on impressions and transactions.
5. Worked on use cases such as concept creation, Sentiment classification, topic modelling , Entity extraction using LLM's like Llama2, GPT4 ,local LLM's.
6. Contributed to creation of Fractal Coursera Data Science Specialization. Worked as an SME for content creation regarding topics like Python , Machin learning.

Data Scientist - AI ML

1.Managed end-to-end delivery of fraud, bureau analytics projects, ensuring effective interaction with business stakeholders.
2. Collaborated with stakeholders on bureau initiatives, achieving a 30% uplift in risk classification for new-to-bank customers applying for two-wheeler loans.
3. Participated in Proof-of-Concept (POC) projects with bureaus to assess product testing and enhance understanding of bureau data quality.
4. Built machine learning models for document and profile fraud identification, as well as early delinquency detection in portfolios like consumer durables and two-wheeler loans ,got 35% lift for TWL & 32% lift for CD on existing F.I.F.
5. Handled ad-hoc assignments, including model tracking, identification of fraudulent merchants, and customer segmentation for risk mitigation in auto loans.

Data scientist 

1. Have delivered projects regarding identifying the Attrition , segmenting and targeting customers using supervised and unsupervised ML techniques.
2. Did work on time series forecasting for predicting future transactions in python using Arima modelling ,helped stakeholders with model of 94% accuracy.
3. Worked on ICR ,OCR part with the help of deep learning techniques, helped the internal invoice text extraction and saved time worth of 2 FTE/week.
4. Worked on NLP and created a chatbot using Rasa framework in python

Senior Associate , Statistical Analysis (Data Scientist)

I believe a mentor has a job to motivate his mentees so that they can overcome their fears , I will not lecture you here with philosophical quotes but we will surely find a practical way to deal with this fear.

We will work around assignments so that you will develop a sense of accountability for delivering a task.

Emotional & mental support is critical in any journey & I understand the importance. I am here to listen and can talk to you on your issues 

If you don't manage the time ,time will kill you as brutal as it sounds but truth ultimately. So we will figure out a plan to manage your time along with your day to day engagement/ responsibilities.

We will start off by understanding where your interest lies , what are your key strengths and perhaps will work around those lines. Remember data career is like ocean. Diving in ocean is not advisable ,you need to pick your goal and work around that precisely for a successful transition.

We can work on your roadmap and track it with the help of deadlines so that you can major your progress and I can measure effectiveness of my mentoring...

I will make sure to share the relevant material,blogs ,videos  required for study purposes 

We will make sure that all the progress is being tracked.

In any interview along with technical skills it is very important to present yourself in neat manner so that your thought clarity reaches the interviewer and most of the times people ignore or lack this skill. So let's talk about this pain area.

Will be helping you with communication skills you require in general for salary negotiation , initial profile introduction rounds & so on.

Yes ,Job application needs to be made precise and that requires strategy. Let's discuss this in detail.

Varun Tushar Raste

Resume is the most basic way of entering any organization even before you show up. Your resume is your first impression and if it's not proper then you might face hardships. Dont sorry I can review your resume and we can discuss what all things you can add or modify.

I have understood the importance of maintaining a proper linkedin profile as I have cracked most of my career opportunities with the help of linkedin only. So let's discuss on how we can setup your LinkedIn profile in order to improve your job gaining chances.

Machine learning is an essential skills which is required for any data scientist in general. So let's get started with algorithms.

Machine Learning

NLP is useful because there is a lot of data which is in the form of text  ,have you ever wondered how a machine detects if text is positive or negative ? Let's find it out then 

Natural Language Processing (NLP)

Deep learning is an advance extension of machine learning. It's just a set of neural networks which leverage heavy data and give us good performance.

Deep Learning

Python is a powerful and versatile programming language that can be used to develop solutions for many different problems. It is easy to learn and understand, and has a wide range of libraries and frameworks for advanced development.

Python

SQL is a powerful language for retrieving, manipulating, and managing data. It is essential for data analysis, report generation, and decision-making, making it a valuable skill to learn for any data-driven role.

Predictive modelling is an important skill to learn as it provides insights into future outcomes based on historical data, allowing us to make better informed decisions and plans.

Predictive Modelling

Leadership & Communication are essential skills to learn as they help you to understand yourself and others better, bring people together and help to create a successful team to achieve great results.

Leadership & Communication

PySpark is an important skill to learn because it is a powerful tool for data analysis and machine learning. It enables efficient and scalable data processing, making it a valuable skill for data scientists.

PySpark

databricks

time series forecasting



Teamwork is an important skill to learn as it teaches how to work together effectively to achieve a common goal, develop communication and problem solving skills, build trust and create a positive working environment.

Teamwork



Artificial Intelligence is an important skill to learn because it is the future of technology. AI can help solve complex problems quickly and efficiently, and it can help people make informed decisions faster. AI can also be used to automate tedious tasks, which can increase productivity.

Artificial Intelligence



Neural Networks are a powerful tool for AI, allowing for the creation of smart and efficient models. They can be used for a variety of tasks such as image processing, speech recognition and natural language processing. With the growing interest in AI, Neural Networks are becoming increasingly important for any aspiring AI professionals.

Neural Networks



TensorFlow is an important skill to learn because it is a powerful library for building and training machine learning models. It allows developers to quickly and easily develop powerful models that can be deployed to a variety of platforms.

TensorFlow



Advance Analytics helps to make decisions based on data and turn data into actionable insight. It is a key skill to acquire for any organisation looking to stay ahead of the competition and make informed decisions.

Advance Analytics



Statistics is important as it enables us to identify trends, make predictions, and gain valuable insights from data to make more informed decisions.

Statistics



Prediction algorithms are important to learn because they allow us to make accurate predictions about future outcomes based on data from the past. This helps us to make informed decisions and maximize our chances of success.

Prediction Algorithm



Business Analysis is an important skill to learn as it enables an individual to gain a better understanding of the processes and systems used in business, allowing them to spot opportunities for improvement and add value to the organisation.

Business Analysis



Analytics is an important skill to learn as it provides valuable insights into data, helping to make informed decisions and create strategies that are based on evidence. It is a vital skill in today’s data-driven world.

Analytics



R Programming is an important skill to learn as it is used for data analysis, statistical computing, and creating data visualizations. It also allows for automated processing of large datasets. All of these skills are essential for today's data-driven world.