Engagement Director 20210

Job Title: Engagement Director

Worksite Location: 111 Town Square Pl., Suite 1203, Jersey City, NJ 07310

 Job Description:

1. Building and interpreting machine learning models on real business data from the SigView platform, e.g. Logistic Regression, Boosted trees (Gradient boosting), Random Forests, and Decision Trees.
2. Identifying data sources, integrating multiple sources or types of data, and applying data analytics expertise within a data source in order to develop methods to compensate for limitations and extend the applicability of the data.
3. Extracting data from relevant data sources, including internal systems and third-party data sources, through manual and automated web scrapping, and validating third-party metrics by cross-referencing various syndicated data sources.
4. Determining which numerical variables are to be used in the same form as they are from the raw datasets; categorized into buckets; and used to create new calculated numerical variables.
5. Performing exploratory data analysis using PySpark to finalize the list of compulsory variables that will be imperative to solve the business problem.
6. Transforming formulated problems into implementation plans for experiments by applying and creating the appropriate data science methods, algorithms, and tools, and statistically validating the results against biases and errors.
7. Working with the offshore teams, post data preparation to identify the best statistical model/analytical solution that can be applied to the available data to solve the business problem and derive actionable insights.
8. Collating the results of the models and preparing detailed technical reports that show how the models can be used and modified for different scenarios in the future to develop predictive insights.
9. Developing multiple reports to facilitate generation of various business scenarios and providing features for users to generate scenarios.
10. Interpreting results of tests and analyses to develop insights into formulated problems within the business/customer context and providing guidance on risks and limitations.
11. Acquiring and using broad knowledge of innovative data analytics methods, algorithms, and tools, including Spark, Elasticsearch, Python, Databricks, Azure, Power BI, Azure Cloud services, LLMs-Gen AI, and Microsoft Suite.
12. Applying concepts from scientific literature on the analysis of scalability and applicability to formulated problems.

May telecommute.

Travel: Requires 10% travel nationally to meet with clients.

Minimum Requirements:

Bachelor’s (or foreign educ. equiv.) Degree in Electronics Engineering, Computer Engineering, Data Analytics, Computer Science, or a related field plus five (5) years (post degree, progressive) experience in the job offered or related occupation.

Special Skill Requirements: 

1. Applying statistical methods to validate results and support strategic decisions.
2. Building and interpreting advanced machine learning models, including Logistic Regression, Random Forests, and Gradient Boosting.
3. Use of Python, Scikit-Learn, XGBoost, Databricks, Excel, and Azure Machine Learning for data preparation and model validation.
4. Integrating diverse data sources using data analytics techniques to address limitations and enhance data quality.
5. Performing data analysis and predictive model development using AI/ML algorithms.
6. Natural language processing (NLP) techniques, LLMs, Gen AI, Azure ML, GitHub, and SQL.
7. Mathematical knowledge in Statistics, Probability, Differentiation and Integration, Linear Algebra and Geometry.
8. Data Science libraries, including NumPy, SciPy and Pandas.
9. Azure Data Factory for data pipeline design and real-time Extract, Transform, and Load (ETL).
10. NLTK, Spacy, Hugging Face Transformers, Azure Text Analytics, OpenAI, Word2Vec, and BERT.
11. Milvus, FAISS, Azure Cosmos DB, Confluence, and Power BI.

Base Salary: $171,000 to $190,000 per annum. Benefits include sick and vacation pay. 40 hours per week; M-F

Notice of the Filing of the Application for Permanent Employment Certification. Please contact Piyush Khemka, VP, Business Operations, at: 111 Town Square Pl., Suite 1203, Jersey City, NJ 07310, with applications, comments, or questions. This notice is being provided as a result of the filing of an Application for Permanent Employment Certification (ETA Form 9089). This Notice of Filing will be posted between 30 and 180 days before filing the permanent labor certification application. The employer intends to permanently employ a foreign national in the job opportunity described above. Any person may provide documentary evidence bearing on the application to: United States Department of Labor, Employment and Training Administration, Office of Foreign Labor Certification, 200 Constitution Avenue NW, Room N‐5311, Washington, DC 20210.