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Data scientists are in huge demand for the skill they bring to the table. Businesses, medium or large scale expect to grow bigger with the insights provided by them. Analyzing the business from every angle progressively becomes possible with the help of a data scientist. So What is a Data Scientist Job about?
Data Scientist Responsibilities
They have to work hand in hand with stakeholders for understanding their objectives and how data can help in achieving them. The Data Scientist Job requirements include the following
1. Gathering data and prompting the proper questions for further data cleaning and processing.
2. Conducting data investigation and exploratory analysis after storing and integrating data.
3. Implementing techniques including machine learning, artificial intelligence and statistical modeling, after selecting potential algorithms and models.
4. Showcasing the final outcome after improvising and measuring the results, doing necessary adjustments if required and repeating the procedure.
Different Job Profiles in Data Science
These are some common Career paths, which includes the data scientist role
1. Data Architect: responsible for creating, designing and managing the data architecture of an organization.
2. Data Analyst: maneuvering massive data sets for recognizing trends and making significant conclusions for insights and business-related decisions.
3. Business Intelligence Expert: gathering patterns from the data.
4. Data Scientist: performs data modeling for creating predictive modeling and algorithms, also deals with customized analysis.
5. Data Engineer: they deal in organizing, cleaning and aggregating data from diverse sources, further shifting them to data warehouse.
Data Scientist at Microsoft
Microsoft has a sub-department named applied sciences and data that is classified under engineering. Teams are divided based on the major titles which include machine learning engineer, data scientist and applied scientist. These are some general functions:
1. Writing code to be implemented by data scientists for machine learning algorithms. Also, for forwarding the models towards production.
2. Dealing with experimentation, product features, metrics, customers (direct or indirect), technical issues.
Data scientist jobs at Microsoft are team-based, for instance, one team is dedicated to machine learning while the other deals with analytics.
Data Scientist required skills at Microsoft
General requirements are Bachelor/ Master Degree in a quantitative field. For a mid-level role, a 2-year experience is preferred.
1. Prior experience in reinforcement Learning, casual inference, DNN, time series, network Analysis, NLP or in other relative fields.
2. Substantial experience in Azure or AWS, the cloud-based architecture.
3. Proficiency in R, Python, SQL, NumPy, Spark, SciPy or C# or similar numerical programming language.
Data Scientist at Amazon
Like any other global firm, Amazon has departments set up for everything. Data scientists join a specific team, but regardless of that, they all have some similarities. It includes a background in Statistics, programming, analytics, mathematics, computer science, and scripting languages like Java, Python etc. They also possess a thorough understanding of artificial intelligence and machine learning algorithms. Some specializations available include:
1. Amazon Web services: the data scientist assists AWS customers by creating ML models and tending their business requirements.
2. Alexa: here the data scientist is expected to be proficient in natural language processing plus information retrieving. This is needed for training the AI to comprehend the commands in several languages.
3. Demand forecasting: the data scientist allotted here has to develop algorithms that comprise learning from huge data like product attributes, prices, similar products, promotions for predicting the demand of millions of products on Amazon.
They are expected to collaborate with information architects, marketers, data engineers, designers, software developers.
Levels of Data Scientist at Amazon
1. Entry-level: This position is often held by those who are still studying or are there for internships. They need proficiency in one language PHP, Java or Python plus some working knowledge of SQL. They should be adept at dealing with analytical problems via a quantitative approach.
2. Senior-level: Apart from management roles, this level requires degrees in Statistics, engineering, computer science, economics, mathematics. For a specialized role, expertise in computer vision and natural language processing can be expected along with work experience in analytics.
Data Scientist at Google
The data scientist has to be either product-oriented or analysis-oriented.
Product Analyst
They usually have domain and other specialized knowledge. They work on:
1. Consumer’s different choices and sentiments
2. Product Popularity and failure reasons
3. Target market statistics
4. Datasets (external and internal)
Quantitative Analyst
They generally have degrees in mathematics, quantitative study, and Statistics. They work on:
1. Product research
2. Forecasting customer lifetime value
3. A/B experiments
4. Modifying search algorithms
5. Estimating future internet reach in different countries
6. Statistical modeling
Data Scientist Responsibilities at Google
1. Inspecting and improvising the products. Collaborating with engineers and analysts. Working on big data sets
2. Conducting requirements specifications, ongoing deliverables, data gathering, processing, presentations and analysis
3. Implementing optimization and forecasting, R&D Analysis. Doing cost-benefit recommendation, communicating inter-functionally
4. Conducting presentation findings with experimental analysis, displaying quantitative information related to stakeholders.
5. Understanding metrics and data structures, recommending necessary product development changes.
6. Prototyping Analysis pipelines and building iteratively for insights.
Data Scientist Salaries
These are the mean salaries in different firms for data scientists.
1. The average Data Scientist Microsoft salary is around 25 lakhs + Stocks annually
2. The average Data Scientist Amazon salary is around 23 lakhs + Stocks yearly
3. The average Data Scientist Google salary is around 24 lakhs + Stocks for a year
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