Role overview

Qualifications

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field
3-4 years of experience on data science projects including hands-on supervised and unsupervised learning
Proficiency in statistics, machine learning, deep learning, natural language processing, EDA, and Power BI
Hands-on experience with Python/R libraries (NumPy, Pandas, Matplotlib/Seaborn, Scikit-Learn, NLTK, Streamlit, TensorFlow, Keras) and familiarity with cloud platforms (AWS, GCP, Azure)

Responsibilities

Collaborate with senior data scientists and business stakeholders to understand project requirements and define analytical objectives
Collect, clean, and preprocess large datasets to ensure data quality and integrity
Develop and implement machine learning algorithms to solve complex business problems, including feature engineering and model evaluation
Communicate findings clearly to stakeholders, monitor and refine models, and stay up-to-date with advances in data science and AI

Key facts

Remote from: Anywhere
Full time
Mid-level (2-5 years)
Data Scientist
English

Hard skills

SQL (Programming Language) Python (Programming Language) Statistical Modeling Machine Learning StreamSets Keras (Neural Network Library) Model Validation Microsoft Visual Studio Natural Language Processing (NLP) Pandas (Python Package) AWS Cloud Services Unsupervised Learning Matplotlib (Python Package) Deep Learning R (Programming Language) Machine Learning Exploratory Data Analysis Feature Engineering PyCharm Data Cleansing Google Cloud Platform (GCP) Microsoft Azure Statistics Data Quality Scikit-Learn (Python Package) Jupyter Power BI Seaborn Data Collection NumPy (Python Package) Data Preprocessing Feature Selection HyperText Markup Language (HTML) Artificial Intelligence TensorFlow NLTK (NLP Analysis) Supervised Learning Tableau (Business Intelligence Software) Apache Spark Apache Hadoop Stakeholder Communications

Other skills

Communication
Analytical Skills
Teamwork
Microsoft Office
Problem Solving

About the company

KiE Square Analytics

KiE Square is an Advanced Data Science, Data Engineering and Data Visualization Corporation that believes in creating High Speed Impact for its Clients. Some Key Stats about the Company - Implemented more than 200 Data to Decisions programs for several Global Corporations as well as Regional Leaders. - Brings Value Advantage to its clients through a Global Delivery Model - 15 successful years of Analytics Program Design & Implementation - Program Delivery Success is 100% and well supported by client testimonials. - High Quality workforce with Great Commitment and E-Quotient - Founded by alumni of IIM Ahmedabad (#1 B-School of India) with nearly two decades of experience in US, Europe and India Top Industries: Consumer goods | Retail | Financial Services | Healthcare | Federal Taxes Top Capabilities: Data Engineering | Data Science | Data Visualization Top Solution Areas: Revenue Analytics | CRM Analytics | Risk Analytics | Digital Transformation | Operations Analytics | Taxation Analytics Locations: Delhi NCR | US | Singapore | UAE

Company details

Company size51 - 200

Links

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Job description

This is a remote position.

Job description- Data Scientist

KiE Square is a leading AIML Company that provides advanced Data Science/Data Engineering Solutions to its

clients and drives their Business Intelligence Transformation.

We invite you to join our Core Team of Data Scientists, Data Engineers and AIML Developers who have a sharp

analytical bent, have delivered multiple high value projects while handling large datasets & have built

Predictive Models.

In this role you will leverage your strong collaboration skills and ability to extract valuable insights from highly

complex data sets to ask the right questions and find the right answers.

Responsibilities:

 Collaborate with senior data scientists and business stakeholders to understand project requirements and

define analytical objectives.

 Collect, clean, and preprocess large datasets to ensure data quality and integrity.

 Apply statistical analysis techniques and develop predictive models to identify patterns, trends, and

insights.

 Conduct exploratory data analysis to uncover hidden patterns and correlations.

 Develop and implement machine learning algorithms to solve complex business problems.

 Perform feature engineering and selection to optimize model performance.

 Evaluate and interpret model results, and present findings to stakeholders in a clear and concise manner.

 Continuously monitor and refine models to ensure accuracy and effectiveness.

 Stay up-to-date with the latest trends and advancements in data science, machine learning, and artificial

intelligence.

 Have a natural ability to take responsibility.

Qualifications:

 Bachelor's & or Master's degree in Data Science, Computer Science, Statistics, or a related field.

 3-4 years of experience of minimum 2 projects in Data Science that include hands on use of Supervised &

Unsupervised learning.

 Application-level experience in Statistics | Machine Learning | Deep Learning | Natural Language

Processing | EDA | Power BI | Problem Solving |AI

 Cloud: AWS|GCP| Azure

 Languages: Python |R| SQL | HTML

 Tools: Office | Jupyter | Colab | VS Code | Pycharm

 Familiarity with Big Data frameworks and visualization tools (Power BI, Hadoop, Spark, Tableau)

 Excellent problem-solving and analytical skills.

 Ability to work both independently and collaboratively in a fast-paced environment.

 Strong communication skills to effectively present findings and insights to non-technical stakeholders.

Key Skills- Python, R, Machine Learning, SQL, Power BI, Statistical/ Predictive Modelling