Job Profile :

- Understand Business Requirements and identify opportunities for ML Solutions

- Develop data solutions and insights using data modeling, machine learning, statistics and analytics.

- Ensure implementation of best suited ML solution for the business problem with data accuracy, consistency and performance in mind

- Deploy ML and DL models to production

- Optimize the model performance, latency, memory and throughput

- Conduct inference testing on hardware, version control of models, metadata, experiments

- Design and develop AI solutions applying Machine Learning models, Deep Learning, Classification models, statistical methods and NLU/NLP

- Develop processes and tools to monitor model performance and data accuracy.

- Analyze the data trends and recommend action/ steps to the leadership of the business divisions or control divisions to improvise their performance.

- Conduct analysis of respective business & provide insights with respect to leading and lagging indicators within business to enable effective decision making.

- Present information using data visualization techniques.

- Look for continuous optimization and improvements.

- Develop ML SMEs within the organization.

Primary Skills :

- Good programming Skills and analytical abilities

- Structured Thinking and Strong Problem-Solving Skills

- Coding Proficiency in AI Programming languages like Python, R, Java etc.

- Python libraries such as Spark, pandas, scikit, etc.

- Identifying, extracting, and creating meaningful features from raw data to improve model performance, including techniques like scaling, normalization, and polynomial features.

- Deep understanding of Principal Component Analysis (PCA), t-SNE, and LDA will be preferable.

- Applying statistical tests such as ANOVA, chi-square, and t-tests.

- Optimizing machine learning models through hyperparameter tuning techniques like Grid Search, Random Search, and Bayesian Optimization.

- Evaluating model performance using cross-validation, ROC curves, AUC, precision-recall, and confusion matrix to ensure robustness and generalization.

- Analyzing and forecasting time-dependent data using ARIMA, SARIMA, and LSTM models, as well as handling seasonality and trend components.

- Applying regularization methods such as L1 (Lasso), L2 (Ridge), and Elastic Net.

- Utilizing Bayesian methods for probabilistic modeling, including experience with tools like PyMC3 or Stan for implementing Bayesian networks and hierarchical models.

- Implementing Classic MLs, XGBoost, LightGBM, SVM, KNN and stacking to enhance model accuracy and robustness.

- Good functional and hands on knowledge in ML Techniques and tools like TensorFlow, Keras, Apache MxNet.

- Strong Math Skills (Multivariable Calculus and Linear Algebra).

- Exposure to GEN AI such as ChatGPT, Lama, Amazon bedrock, gemini etc.

- Experience working with RESTful API and general SOA Architecture.

- Good understanding and experience in ML cloud Platforms like Amazon SageMaker, H2O.ai etc.

- Expertise in industry leading design and architecture principles

Secondary Skills :

- Familiarity with Cloud Architecture, Development of AI/ ML based solutions on Cloud (AWS/ Azure etc.)

- Strong knowledge of storage data architecture or data lakes

- Interpersonal and Leadership Skills and strong business acumen

- Able to collaborate with cross functional teams.

- Certifications associated to AI/ML will be an added advantage.

- Financial Domain knowledge is another advantage.

- Has good exposure and hands on experience to BI Tools like Power BI, Tableau, Apache superset or equivalent visualization tools

- SQL, ETL, Data Mining, Building Statistical Models for Large Datasets and BI/ Data Visualization tools.

Competency :

- Identify areas to implement ML solutions in the current application stack.

- Lead architecture and development of ML solutions for the organization.

- Solid knowledge and hands on experience in analyzing large amounts of information to find patterns and BI solutions.

- Usage of Statistics and ML Algorithms to arrive at custom data models to provide accurate outputs.

- Resolve complex technical issues in implementation of AI and ML Solutions.

- Ability to work effectively under pressure to meet critical deadlines.

- Presenting results in a clear and concise manner

- Excellent Verbal and Written - Communication and Presentation Skills.

- Ability to upskill in relevant area