Logistic regression Jobs in Bangalore (Bengaluru)

Roles and Responsibilities:

• Work with stakeholders across the organization to identify opportunities for leveraging company data to drive business solutions.

• Mine and analyze data from company databases to drive optimization and improvement of processes, marketing techniques and business strategies.

• Develop custom data models and algorithms to apply to data sets.

• Use predictive modeling to increase and optimize the business process and solutions.

• Research and development of AI algorithms and their applicability in business-related problems to build intelligent systems

Desired Profile:

• Need to have experience in data analytics, descriptive analytics and predictive analytics

• Need to have experience with regression/classification models: Linear Regression, Logistic Regression, Decision Trees, Random Forest, Neural Networks and ML Models

• Need to have experience coding in Python, R, SQL, Java, C and C++ • Experience using AI/ML tools available from cloud service providers like AWS/AZURE/GCP including TensorFlow, SageMaker and Azure ML • Experience with Data Visualization

• Strong problem-solving skills with an emphasis on product development.

• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.

• Proven track record of supporting global clients or internal stakeholders in data science projects.

• Technical knowledge in Artificial Intelligence (AI), image processing and/or video analytics • Good understanding of the latest research and technologies in Artificial Intelligence

Good to Have:

• Need to have background/education/experience in Statistics • Experience in working across multiple geographic borders and time zones

• Outstanding spoken and written communication skills: able to deal confidently, tactfully and appropriately with people of different disciplines and at all levels of the organization.

• Communicate technical concepts effectively a to non-technical audiences

• Able to build strong relationships with multiple global stakeholders quickly via virtual tools, listen, understand and respond to any concerns.

• Comfortable working within a large and complex environment with multiple stakeholders and interest groups. Ability to motivate and influence others to achieve results.

• Use data to develop machine learning models that optimize decision making in Credit Risk, Fraud, Marketing, and Operations
• Implement data pipelines, new features, and algorithms that are critical to our production models
• Create scalable strategies to deploy and execute your models
• Write well designed, testable, efficient code
• Identify valuable data sources and automate collection processes.
• Undertake to preprocess of structured and unstructured data.
• Analyze large amounts of information to discover trends and patterns.

Requirements:

• 2+ years of experience in applied data science or engineering with a focus on machine learning
• Python expertise with good knowledge of machine learning libraries, tools, techniques, and frameworks (e.g. pandas, sklearn, xgboost, lightgbm, logistic regression, random forest classifier, gradient boosting regressor, etc)
• strong quantitative and programming skills with a product-driven sensibility

• Use data to develop machine learning models that optimize decision making in Credit Risk, Fraud, Marketing, and Operations
• Implement data pipelines, new features, and algorithms that are critical to our production models
• Create scalable strategies to deploy and execute your models
• Write well designed, testable, efficient code
• Identify valuable data sources and automate collection processes.
• Undertake to preprocess of structured and unstructured data.
• Analyze large amounts of information to discover trends and patterns.

Requirements:

• 1+ years of experience in applied data science or engineering with a focus on machine learning
• Python expertise with good knowledge of machine learning libraries, tools, techniques, and frameworks (e.g. pandas, sklearn, xgboost, lightgbm, logistic regression, random forest classifier, gradient boosting regressor etc)
• strong quantitative and programming skills with a product-driven sensibility

About antuit.ai

Antuit.ai is the leader in AI-powered SaaS solutions for Demand Forecasting & Planning, Merchandising and Pricing. We have the industry’s first solution portfolio – powered by Artificial Intelligence and Machine Learning – that can help you digitally transform your Forecasting, Assortment, Pricing, and Personalization solutions. World-class retailers and consumer goods manufacturers leverage antuit.ai solutions, at scale, to drive outsized business results globally with higher sales, margin and sell-through.

Antuit.ai’s executives, comprised of industry leaders from McKinsey, Accenture, IBM, and SAS, and our team of Ph.Ds., data scientists, technologists, and domain experts, are passionate about delivering real value to our clients. Antuit.ai is funded by Goldman Sachs and Zodius Capital.

The Role:

Antuit is looking for a Data / Sr. Data Scientist who has the knowledge and experience in developing machine learning algorithms, particularly in supply chain and forecasting domain with data science toolkits like Python.

In this role, you will design the approach, develop and test machine learning algorithms, implement the solution.  The candidate should have excellent communication skills and be results driven with a customer centric approach to problem solving.  Experience working in the demand forecasting or supply chain domain is a plus. This job also requires the ability to operate in a multi-geographic delivery environment and a good understanding of cross-cultural sensitivities.

Responsibilities:

Responsibilities includes, but are not limited to the following:

• Design, build, test, and implement predictive Machine Learning models.
• Collaborate with client to align business requirements with data science systems and process solutions that ensure client’s overall objectives are met.
• Create meaningful presentations and analysis that tell a “story” focused on insights, to communicate the results/ideas to key decision makers.
• Collaborate cross-functionally with domain experts to identify gaps and structural problems.
• Contribute to standard business processes and practices as part of a community of practise.
• Be the subject matter expert across multiple work streams and clients.
• Mentor and coach team members.
• Set a clear vision for the team members and working cohesively to attain it.

Qualifications and Skills:

Requirements

• Experience / Education:
  • Master’s or Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, Statistics, Applied Mathematics or other related 
• 5+ years’ experience working in applied machine learning or relevant research experience for recent Ph.D. graduates.
• Highly technical:
• Skilled in machine learning, problem-solving, pattern recognition and predictive modeling with expertise in PySpark and Python.
• Understanding of data structures and data modeling.
• Effective communication and presentation skills
• Able to collaborate closely and effectively with teams.
• Experience in time series forecasting is preferred.
• Experience working in start-up type environment preferred.
• Experience in CPG and/or Retail preferred.
• Effective communication and presentation skills.
• Strong management track record.
• Strong inter-personal skills and leadership qualities.

Information Security Responsibilities

• Understand and adhere to Information Security policies, guidelines and procedure, practice them for protection of organizational data and Information System.
• Take part in Information Security training and act accordingly while handling information.
• Report all suspected security and policy breach to Infosec team or appropriate authority (CISO).

EEOC