VIS & BI Strategy Practitioner

Project Role :VIS & BI Strategy Practitioner


Project Role Description :Develop a VIS/BI vision, business case, and modernization strategy; discover and assess VIS/BI opportunities; identify industry- and function-centered VIS/BI use cases; guide clients on industry and function relevant measures and metrics; develop a VIS/BI roadmap and operating model; help drive adoption, decision making and behavior change; measure VIS/BI value.

Must have skills :Machine Learning


Good to have skills :NA
Minimum

7.5 year(s) of experience is required


Educational Qualification :BE

Summary:You will be responsible for utilizing data science methodology to inform the design research process. Your typical day will involve employing statistical and quantitative data analysis to enhance solution development.
Roles & Responsibilities:

Having broad technology background, with focus on developing software applications in Python for production ready applications

Writing container-based code and testing code, debugging programs and integrating applications with third-party web services, deployment Work with cross functional team to scale the architecture supporting

AI models Support data needs for model training/ensemble the models Architecture, security reviews, NFRs Experience in Agile, DevOps, driving best practices

Lead the development and deployment of advanced machine learning models using Python and associated libraries like Pandas, NumPy, and Scikit-learn.

Conduct detailed analysis of complex data sets, employing statistical methodologies and data munging techniques for actionable insights, alongside a robust understanding of statistical analysis and machine learning algorithms.

Collaborate with cross-functional teams, applying expertise in diverse machine learning algorithms, including experience in implementing various algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms.

Communicate technical findings effectively to stakeholders, utilizing data visualization tools like Tableau or Power BI for clarity.

Stay updated with the latest advancements in machine learning and data science, integrating innovative approaches for sustained competitive advantage, including experience with TensorFlow, Natural Language Processing (NLP), and Big Data technologies.
Professional & Technical Skills:

Using APIs in python Flask, Falcon or Django, Kafka ML and python libraries as scikit-learn, numpy and pandas.

Machine learning, Deep learning, Image Processing Familiarity with Apache SOLR, MongoDB

Familiarity with Celery, Rabbit MQ for background task queues Data pre-processing techniques GIT, Docker, Jenkins, Swagger, Cloud AWS/Azure

Must To Have Skills:Proficiency in Machine Learning.

Good To Have Skills:Experience with TensorFlow, Natural Language Processing (NLP), and Big Data technologies.

Strong understanding of statistical analysis and machine learning algorithms.

Experience with data visualization tools such as Tableau or Power BI.

Experience in implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms.

Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity.
Additional Information:

The candidate should have a minimum of 7.5 years of experience in Machine Learning.

The ideal candidate will possess a strong educational background in statistics, mathematics, computer science, or a related field, along with a proven track record of delivering impactful data-driven solutions.

Qualifications
BE