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A highly competent data scientist with five years of experience developing a wide range of innovative applications like Credit Card Fraud Detection, Stock Sentiment Analysis Model, and Customer support system.
Ability to use (data) statistics and machine learning for finding complex data patterns that drive meaningful impact on the business.
I am looking for the opportunity to build a challenging career and apply my skills in an innovative and simplify process. I enjoy working in a team and communicating data-driven results.
- Python & R
- NLTK & OpenCV
- SQL & SAS
- SPSS & STATA
- PowerBI & Spotfire
- To predict house prices using time series analysis and neural networks
- Identify factors that predict which employees will have the best performance and which will benefit from a change in their job position using machine learning.
- Designed the information architecture and model of an organization’s assets
- Coordinated with the stakeholders on project progress.
- Involved in the continuous enhancements and finding the best solution.
Data Scientist Consultant
- Predictiing the Stock price using sentiment analysis model.
- Finding the stock market daily patterns and creating a meaningful solution to the business.
- Identifing the Mulit bagger stocks using machine learning and AI
Master of Computer Application
Bachelor of Computer Science
Stock Price Prediction
Use the Sentiment Analysis Algorithms to understand the stock sentiments.
Project: Twitter Sentiment Analysis
Tools: NLTK, Python
Algorithms: Sentiment Analysis
Stock Recommender Systems
Recommender systems have become the most popular feature of the stock market. We have developed a artificial intelegint stock recommender tool using the Deep Neural Networks and classification algorithms
Tools: Python, sklearn
Algorithms: Deep Neural Networks, classification algorithms
Customer Support System
Customer support has become a challenging job for every business. We build a “customer support system” to address and support the needs of the customers.
Tools: OpenCV, Python
Algorithms: Convolution Neural Network and other facial detection algorithms
Career Expert Tips:
What Should Be Included In A Data Scientist Resume?
When you’re writing a resume for a data scientist role, it’s important to make sure that you include the necessary information to help you stand out from the competition. A data scientist resume should highlight your technical and analytical skills, as well as any experience you have in dealing with large datasets. It should also emphasize your ability to interpret and present data in meaningful ways.
Your data scientist resume should include a summary of your professional experience, education, and skills. Your professional experience should list relevant job titles, employers, and dates of employment. If you have any specialized training in data science, be sure to include that as well. Your education section should include the name of your degree, the university you attended, and any honors or awards you may have received.
When it comes to skills, your data scientist resume should list any technical skills you have such as coding languages, database management, and data analytics. You should also include any soft skills you have, such as problem-solving, communication, and collaboration skills. If you have any experience with data visualization or business intelligence tools, be sure to include those as well.
The final section of your data scientist resume should include any relevant certifications, publications, or presentations you’ve done. This is a great way to demonstrate your expertise and show that you’re an active member of the data science community.
Overall, your data scientist resume should provide a snapshot of your skills and experience, as well as any relevant certifications or awards. By taking the time to include the right information, you can ensure that your resume will be an effective tool in helping you to land your next data science role.
What Skills Should I Put On My Resume For Data Scientist?
When writing your resume for a data scientist role, the most important element is to highlight the specific skills that make you uniquely qualified for the position. Because data science is such a broad field, employers look for candidates with a range of skills and experience. To stand out from the competition, you need to showcase your technical competencies as well as soft skills, such as problem solving, communication and collaboration.
The most critical skills to include in a data scientist resume are computer programming, data analysis, data visualization, machine learning, and statistical modeling. To demonstrate your proficiency in these areas, include details about the tools and techniques you have used in the past. For example, you could detail which programming languages you are familiar with and provide an example of a project you have worked on using those languages. Additionally, be sure to include any experience you have with big data platforms, such as Hadoop, MongoDB and Apache Spark.
In addition to technical skills, employers also seek data scientists with strong problem-solving capabilities, as well as strong written and verbal communication skills. To demonstrate these abilities, include details about any projects or initiatives you have worked on that required creative problem-solving, as well as any presentations or reports you have prepared. It is also important to show your ability to work on teams, so be sure to include any work you have done with external stakeholders or in a collaborative environment.
By highlighting the relevant skills and experiences on your data scientist resume, you can ensure that you stand out from the competition and demonstrate your value as a candidate.
What Is The Job Description Of The Data Scientist?
Data science is a rapidly growing field that is in high demand due to the growing need for data-driven insights in business and industry. A Data Scientist is responsible for analyzing complex data sets, developing actionable insights, and communicating those insights to key stakeholders. They are expected to have a wide range of skills from computer programming to data visualization, machine learning algorithms, and more.
Data Scientist roles often demand an in-depth understanding of mathematics, statistics, and computer science, as well as an understanding of the business context in which data is used. The ability to work collaboratively and communicate clearly is also essential in this role. Data Scientists are expected to solve complex problems, create innovative solutions, and influence key decisions in order to effectively drive the success of the organization.
Data Scientists typically have a strong technical background and the ability to analyze data in a meaningful way. They must be able to build predictive models and develop algorithms that can process and transform data into actionable insights. They must also be able to interpret and communicate those insights in a way that is understandable to key stakeholders. It is essential that they are knowledgeable of the latest technologies and trends in the field, and they should also be familiar with a wide range of data sources and tools.
A successful Data Scientist should also have strong problem-solving skills and the ability to think critically. They should be able to develop and execute data-driven strategies, and have the knowledge and skills to be able to effectively explain their findings to others. Lastly, they should have the ability to adapt to changing technologies and trends in the field.
What Is A Good Objective For A Data Scientist Resume?
Writing a data scientist resume can be daunting. It is important to make sure your resume accurately reflects your skills and experience, as this will be your first point of contact with potential employers. One of the most important sections to include in your data scientist resume is the objective.
Your objective statement should be a concise summary of the skills and experiences you can bring to the position. It should provide the employers with an overview of what you have to offer, and should be tailored to the specific job you are applying for. A good objective should be both specific and relevant, illustrating your qualifications and what you can bring to the role.
When crafting your objective statement, be sure to focus on the skills and qualifications the employer is looking for in a data scientist. This could include technical skills such as programming languages and data analysis tools, as well as soft skills like problem solving and communication. By putting this information upfront and clearly showing the employer why you are the best candidate for the job, you can demonstrate that you are the perfect fit for the role.
In addition to focusing on your technical skills, it is important to include a few sentences stating your career goals. Showing that you have an understanding of your own ambitions, as well as the career path the employer is offering, can be a huge plus.
Overall, your objective statement should be an accurate reflection of who you are as a data scientist. By clearly communicating your skills and qualifications, you can show employers that you are the perfect candidate for the job.
What Are The Career Prospects In The Data Scientist?
Data Science is one of the most sought-after career paths in the tech industry. Data Scientists apply their analytical and problem-solving skills to extract business insights from data. They are in demand for their ability to analyze complex data sets and build models to improve performance. With the right skill set, a Data Scientist can develop a successful career.
The job prospects for Data Scientists are extremely encouraging. According to a report by the World Economic Forum, the demand for Data Scientists has grown by over 600 percent in the past five years. This growth is expected to continue as companies of all industries and sizes embrace the power of data-driven insights. Companies are increasingly relying on Data Scientists to help them make strategic decisions, leading to higher job prospects.
The average salary for a Data Scientist is upwards of $90,000 per year, depending on experience and geographic location. Experienced Data Scientists can command a salary of over $130,000 per year. With the right skills and experience, experienced Data Scientists can move up to higher-level positions such as Chief Data Officer, Data Strategist, and Chief Analytics Officer.
Data Scientists must possess the technical skills to extract insights from Big Data, as well as the communication skills to effectively present their findings to stakeholders. Data Scientist must also have experience in predictive analytics and machine learning to create models and algorithms.
Data Scientists have become an indispensable asset for businesses looking to leverage data and make informed decisions. With the right skills and experience, a Data Scientist can enjoy a long and successful career.
Key Takeaways for an Data Scientist resume
As a data scientist, your resume needs to stand out from the crowd to help make a positive first impression. With the right approach, you can make sure your data scientist resume catches the attention of potential employers and highlights your skills and qualifications. Here are the key takeaways for writing a successful data scientist resume:
First, make sure your resume is tailored to the job you are applying for. Highlight the skills and experience that are most relevant to the role you are applying for. This will help ensure your resume is quickly seen and read by the hiring manager.
Second, use a professional format for your resume. Your resume should be visually appealing and easy to read. Make sure to include a summary statement that outlines your experience and outlines the qualities that make you an ideal candidate for the data scientist role.
Third, showcase your experience with data science tools and technologies. List out the specific tools and technologies you have used in your previous roles, and highlight any awards or certifications you have earned in data science. This will help demonstrate your knowledge and experience in the field.
Finally, don’t forget to include data science projects you have worked on in the past. This will show potential employers that you have the skills and experience necessary to work on data science projects. Make sure to include a detailed description of the project and your involvement in it.
By following these key takeaways, you can ensure that your data scientist resume stands out and showcases your qualifications in the best possible way.
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