Modeler

5 days ago

Noida, India Risk Management Solutions (RMS) Full time

**Mandatory skills**:

- Good, applied statistics skills, such as distributions, statistical modelling, statistical testing, regression, machine learning, etc. o Detail-oriented, self-driven quick learner with very strong analytical and problem-solving skills, and a high degree of self-motivation.
- Programming skills in Python, R, Julia, or similar with demonstrated experience of automation.
- Strong documentation skills with experience of working on MS Word, Excel, PowerPoint, and projects. Direct involvement in working with large volumes of data and building, deploying, and measuring predictive analytics models (i.e. LSTM, RNN, SVM, decision tree, clustering, logistic regression, linear and non-linear regression).
- Proficient in Python/R programming skills. Julia programming skill is a plus.
- Understanding of NLP, NLU, and Machine learning/Deep learning methods.
- Databases side SQL, MongoDB, and Neo4j is a plus.
- Knowledge of REST API for deploying ML models.
- Simple UI development paradigms that would enable Text Mining Insights Visualization, e.g., Stream lit, HTML5, CSS3.
- Linux, GPU Experience.

**Experience required**:

- PhD / MSc (Statistics /Operational Research/Mathematics, Applied Mathematics, Econometrics) OR M/BTech (CSE with major as statistics/Mathematical Science) with first-class from reputed institutes/universities.
- Must have more than 2+ Years of relevant experience.
- Communicates analytical and model insights to management that include executive summaries, charts, tables, and graphs and documenting processes, and keeping informed of technological advancements in the field of statistical analysis.
- Compare and analyze provided statistical information to identify patterns, relationships, and problems. Ensuring data integrity by performing rigorous cleaning, error checking, and validation.
- Define and utilize machine learning, deep learning, and statistical methods to solve industry-specific problems in varying fields.
- Analyzing data using statistical techniques, performing statistical tests to determine the soundness of results, and describing, interpreting, and summarizing conclusions.

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