Data Scientist

1 month ago

Bangalore Urban, India HCLTech Full time

Role & Responsibilities:

Applied Math, Statistics, and Scientific Practices

Apply designated quantitative techniques such as time series analysis, optimization and simulation to create and embed appropriate models for analysis and prediction

Provide guidance on matching data sources with relevant applied mathematics and statistical techniques to meet analysis goals

Apply appropriate statistical techniques to available data to discover new relations and offer insight into research problems, helping to improve organizational processes and support decision making

Access and use the statistical tools available within the organization

Data Engineering and Manipulation

Work with data engineers and data scientists to design and deliver products into the organization effectively

Demonstrate understanding of the reasons for cleansing and preparing data before including it in data science products and put reusable processes and checks in place

Access and use a range of architectures (including cloud and on-premise) and data manipulation and transformation tools deployed within the organization

Data Science Innovation

Demonstrate practical knowledge of data science tools and techniques

Develop data science solutions that maximize insight

Identify opportunities for how data science can improve data practices

Delivering Business Impact

Demonstrate an understanding of the organization and the benefits of data science

Collaborate to help identify user needs and develop and deliver data science products

Communicate effectively and present analysis and visualizations tailored to your audience


Developing Data Science Capability

Manage a continuous professional development plan and link to learning objectives and organizational goals

Support data science capability building across the team and wider organization

Confidently talk about the benefits of data science approaches to existing and potential customers

Demonstrate a good understanding of a range of data science techniques, such as machine learning and natural language processing, and you can use them to build data science solutions, including reports, models and dashboards

Ethics and Privacy

Demonstrate an understanding of how ethical issues fit into a wider context and work with relevant stakeholders

Stay up to date with developments in data ethics standards and legislation frameworks, using these to improve processes in your work area

Identify and respond to ethical concerns in area of responsibility

Programming and Build

Write moderate to complex programs and scripts

Show a good understanding of testing methodologies and how to deploy code

Understanding Product Delivery

Demonstrate an understanding of the differences between delivery methods, such as Agile and waterfall, and can choose the most appropriate method to deliver each product

Define the minimum viable product (MVP) and support decisions about priorities

Work with specialists in multidisciplinary teams to smoothly deliver data science products into the organization


Qualifications/Skills:

Required

Master’s or Ph.D. in Computer Science, Statistics, Mathematics, Data Science, or a related field or Bachelor’s with minimum 3 years experience.

Strong academic background with coursework or research in machine learning, AI, statistical modeling, and data analysis.

Proficiency in programming languages such as Python or R for data analysis and machine learning.

Familiarity with libraries and frameworks like TensorFlow, PyTorch, scikit-learn, pandas, and NumPy

Advanced knowledge of statistical methods and techniques

Experience in hypothesis testing, regression analysis, clustering, and classification.

Expertise in machine learning algorithms and techniques

Familiarity with big data technologies and frameworks (e.g., Hadoop, Spark)

Proficiency in SQL, relational database, and NoSQL databases.

Preferred

Strong analytical and problem-solving skills.

Ability to evaluate assumptions and limitations of data.

Excellent verbal and written communication skills.

Experience working collaboratively in interdisciplinary teams.

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