Kaleidofin - Data Scientist - Machine Learning (2-6 yrs)

Responsibilities :

- Partnering with internal business owners (product, marketing, edit, etc. ) to understand needs and develop custom analysis to optimize for user engagement and retention.

- Good understanding of the underlying business and workings of cross-functional teams for successful execution.

- Design and develop analyses based on business requirement needs and challenges.

- Leveraging statistical analysis on consumer research and data mining projects, including segmentation, clustering, factor analysis, multivariate regression, predictive modeling, etc.

- Providing statistical analysis on custom research projects and consulting on A/B testing and other statistical analysis as needed.

- Other reports and custom analysis as required.

- Identify and use appropriate investigative and analytical technologies to interpret and verify results.

- Apply and learn a wide variety of tools and languages to achieve results

- Use best practices to develop statistical and/ or machine learning techniques to build models that address business needs.

- Collaborate with the team to improve the effectiveness of business decisions through the use of data and machine learning/predictive modeling.

- Innovate on projects by using new modeling techniques or tools.

- Utilize effective project planning techniques to break down complex projects into tasks and ensure deadlines are kept.

- Communicate findings to team and leadership to ensure models are well understood and incorporated into business processes.

Requirements :

- Typically has 2 - 6 years of relevant experience.

- Preferred Education : Bachelor's degree in a technical field or equivalent experience.

- Experience in advanced analytics, model building, statistical modeling, optimization, and machine learning algorithms.

- Machine Learning Algorithms : Crystal clear understanding, coding, implementation, error analysis, model tuning knowledge on Linear Regression, Logistic Regression, SVM, shallow Neural Networks, clustering, Decision Trees, Random Forest, XGBoost,

- Recommender Systems, ARIMA Anomaly Detection. Feature selection, hyperparameters tuning, model selection and error analysis, boosting, and ensemble methods.

- Strong with programming languages like Python and data processing using SQL or equivalent and ability to experiment with newer open-source tools.

- Experience in normalizing data to ensure it is homogeneous and consistently formatted to enable sorting, query, and analysis.

- Experience designing, developing, implementing, and maintaining a database and programs to manage data analysis efforts.

- Experience with big data and cloud computing viz. Spark, Hadoop (MapReduce, PIG, HIVE).

- Experience in risk and credit score domains preferred.