KiE Square Analytics - Data Scientist (2-4 yrs)

Job Description :

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 with a natural ability to take responsibility.

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.

- 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.

Qualifications :

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

- Strong understanding of statistical concepts and data analysis techniques.

- Proficiency in programming languages such as Python or R.

- Experience with data manipulation and analysis using SQL and/or NoSQL databases.

- Familiarity with data visualization tools, such as Tableau or Power BI.

- Knowledge of machine learning algorithms and techniques.

- 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.

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

- Experience with cloud platforms such as AWS, Azure, or Google Cloud.

- Knowledge of deep learning frameworks such as TensorFlow or PyTorch.

- Understanding of natural language processing (NLP) techniques.