Vacancy Alert!!! Top Data Science Jobs to Apply for this Week

Top data science jobs

For aspiring data scientists, check out the top data science jobs to apply for this week.

Data science is the hottest job domain in the global data-driven market in 2021. Companies are instigated to recruit employees for multiple data science jobs such as data scientists, data engineers, data analysts, data architects, and many more. These data science jobs help companies use ineffective data efficiently in this competitive world. This is an alert article for vacancies in data science where one can find a favorable and suitable data science job to earn a lucrative salary package throughout a year. Let’s explore some of the top data science jobs to apply for this week.

 

Data Scientist

Webmasters SEO

 

Responsibilities

  • Formulate and lead guided, multifaceted analytic studies against large volumes of data.
  • Interpret and analyze data using exploratory mathematical and statistical techniques based on the scientific method.
  • Coordinate research and analytic activities utilizing various data points (unstructured and structured) and employ programming to clean, massage, and organize the data.
  • Experiment against data points, provide information based on experiment results and provide previously undiscovered solutions to command data challenges.

 

Requirements

  • Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
  • Experience working with ‘big data’ data pipelines, architectures, and data sets.
  • Strong project management and organizational skills.
  • Experience supporting and working with cross-functional teams in a dynamic environment.
  • Experience with big data tools: Hadoop, Spark, Kafka, etc.

 

Data Scientist

Embroker

India

 

Responsibilities

  • Identifying new datasets
  • Researching optimal algorithms to reduce portfolio loss
  • Deriving insights to improve products and customer experience.
  • As a fully remote organization, the candidate will need to be self-driven.

 

Requirements

  • Hands-on experience with data-centric language (Python) not only to manipulate data and draw insights from diverse data sets but also to integrate models into production services.
  • Knowledge and experience in statistical and data mining techniques, e.g., regression, clustering, classification

 

Data Scientist

Boston Consulting Group (BCG)

Delhi

 

Requirements

  • Are comfortable in a client-facing role with the ambition to lead teams.
  • Can distill complex results or processes into simple, clear visualizations. 
  • Can understandably explain sophisticated data science concepts.
  • Comfortable working with modern development tools and writing code collaboratively.
  • Have strong project management skills

 

Senior Data Scientist 

Chargebee

India

 

Responsibilities

  • Explore, find and share actionable recommendations from data
  • Build predictive models and learning systems to enable business strategy
  • Engage with people across functions to surface questions, build hypotheses and test them
  • Influence the organization’s data science strategy
  • Shape the Data Science team through hiring, mentoring, and leading projects

 

Requirements 

  • 7+ years experience in an analytics role
  • 4+ years experience in data science, or similar role
  • Experience in developing machine learning models to run in a production environment
  • Strong communication and narrative skills to present outcomes from analyses and make actionable recommendations
  • Masters or Higher in Computer Science, Statistics, Applied Mathematics, Physics, or other quantitative majors

 

Data Scientist

Tata Consultancy Services

 

 

Responsibilities

  • Programming experience in Python/R & SQL preferably. Exposure to Time Series Forecasting is desirable, but not essential.
  • Working knowledge of the following libraries: numpy, scipy, pandas, scikit learn, matplotlib, seaborn
  • Knowledge of Data Science techniques with evidence of using them on data across supervised & unsupervised learning business problems.
  • Technical understanding of most commonly used algorithms Linear Regressions, Random Forests, SVMs, KNN, K-means, etc.

 

Requirements

  • Focus on Unsupervised Clustering for KNN/K-means, with a wider requirement for Financial Modelling.
  • Past Experience in Finance or Cash Management ideal but not mandatory.

 

Lead Software Engineer – Data Scientist with Python

OpenText

Hyderabad, Telangana

 

Requirements 

  • Experience working with large, multi-dimensional real datasets and real business projects.
  • Good applied statistics skills, such as distributions, statistical testing, regression, etc.
  • Good scripting and programming skills
  • Data-oriented personality
  • Data mining using state-of-the-art methods
  • Extending company’s data with third party sources of information when needed

 

Lead Data Scientist

Chargebee

India

 

Responsibilities

  • Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
  • Develop a use case roadmap for a problem area or capability for the business. Frame the business problem into a Data Science or modeling problem.
  • Extract data from multiple sources. Mine and analyze data from company databases to drive optimization and improvement of products.
  • Work as the data strategist, identifying and integrating new datasets that can be leveraged through the product capabilities and working closely with the engineering team to strategize and execute the development of data products.

 

Requirements

  • Data-oriented personality. Strong problem-solving skills with an emphasis on product development.
  • Good applied statistics skills such as distributions, statistical testing, regression.
  • Good scripting and programming skills. Experience using statistical computer languages, Python,PySpark, R, SQL to manipulate data and draw insights from large data sets.
  • Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, artificial neural networks, and their real-world advantages or drawbacks. Knowledge of deep learning techniques is a plus.
  • Experience with common data science toolkits such as R, NumPy, Pandas, Scikit-learn, TensorFlow, Keras, etc.
  • Experience with data visualization tools such as D3.js, GGplot.

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