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About the job
About the Company:
DataCouch is one of the Leading Training, Staff Augmentation & Consultancy providers, working within the most coveted domains of the IT market such as Data Engineering, Big Data Analytics, Data Science, Machine Learning, Artificial Intelligence, DevOps, Cloud Computing, Robotics Process Automation and many more. With a mission to work dedicatedly towards building an innovative and quality-conscious global organization encompassing the interests of customers, instilling values in employees, and returns for stakeholders.
About the Role:
A short paragraph summarizing the key role responsibilities.
Responsibilities:
Develop, train, and implement predictive models and algorithms to drive business solutions.
Analyze complex data sets to identify trends, patterns, and insights that can influence business decisions.
Perform data mining to discover data patterns and trends.
Develop and maintain advanced reporting, analytics, dashboards, and other BI solutions.
Collaborate with stakeholders to gather requirements and deliver reports and analyses that meet business needs.
Provide support for analytics initiatives by cleaning and structuring data appropriately.
Stay updated with industry trends and advancements in data analytics and visualization technologies.
Collaborate with cross-functional teams to understand business needs and provide data-driven solutions.
Evaluate model performance and iteratively improve on existing methodologies.
Document and present model processes, insights, and recommendations to stakeholders.
Qualifications:
Bachelor's and Master’s degrees in Data Science, Computer Science, Statistics, or a related field.
Required Skills:
Proficient in Python and familiar with key data science libraries (Pandas, Scikit-Learn, TensorFlow, or PyTorch).
Strong understanding of all complex machine learning algorithms not limited to decision trees, random forests, and gradient boosting machines.
Competence in data preprocessing, cleaning, and analysis.
Familiarity with data cleaning, transformation, and preprocessing techniques.
Experience with SQL and possibly some NoSQL databases for data querying and manipulation.
Basic knowledge of data visualization tools like Matplotlib and Seaborn.
Strong skills in SQL for data extraction, and the ability to work with complex database systems.
Advanced knowledge of analytical tools and software such as Excel, Tableau, or more specialized software depending on the industry (e.g., SAS, SPSS).
Experience with data visualization and the ability to create interactive dashboards.
Vast knowledge of NLP, Deep Learning, Machine Learning, Knowledge of genAI with implementation knowledge (LLM, fine tuning RAG implementation) and many more.
Familiarity with cloud services (AWS, Azure, Google Cloud) for data processing and storage.
Preferred Skills:
Certifications (Preferred): AWS Certified Data Analytics – Specialty, Google Professional Data Engineer, Microsoft Certified: Azure Data Scientist Associate
Pay range and compensation package:
Pay range or salary or compensation
Equal Opportunity Statement:
Include a statement on commitment to diversity and inclusivity.