85 Decision Tree Jobs - Page 4

Evaluate model development data quality, methodology Perform proper documentation Conduct in-depth analysis of large data sets and support the review and maintenance process of relevant models and model validation documentation. Required Candidate profile 2+ years experience in model development or model validation experience in the retail section of a U. S. financial services/banking hands-on and proven experience utilizing Python, Spark , SAS, SQL,

Job Title - Data Scientist and Analytics Level 7:Manager Ind & Func AI Decision Science Manager S&C Management Level:07 - Manager Location Bangalore/Gurgaon/Hyderabad/Mumbai Must have skills: Technical (Python, SQL, ML and AI), Functional (Data Scientist and B2B Analytics preferably in Telco and S&P industries) Good to have skillsGEN AI, Agentic AI, cloud (AWS/Azure, GCP) Job Summary : About Global Network Data & AI:- Accenture Strategy & Consulting Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition About Comms & Media practice The Accenture Center for Data and Insights (CDI) team helps businesses integrate data and AI into their operations to drive innovation and business growth by designing and implementing data strategies, generating actionable insights from data, and enabling clients to make informed decisions. In CDI, we leverage AI (predictive + generative), analytics, and automation to build innovative and practical solutions, tools and capabilities. The team is also working on building and socializing a Marketplace to democratize data and AI solutions within Accenture and for clients. Globally, CDI practice works across industry to develop value growth strategies for its clients and infuse AI & GenAI to help deliver top their business imperatives i.e., revenue growth & cost reduction. From multi-year Data & AI transformation projects to shorter more agile engagements, we have a rapidly expanding portfolio of hyper-growth clients and an increasing footprint with next-gen solutions and industry practices. Roles & Responsibilities: Experienced in Analytics in B2B domain. Responsible to help the clients with designing & delivering AI/ML solutions. He/she should be strong in Telco and S&P domain, AI fundamentals and should have good hands-on experience working with the following: Ability to work with large data sets and present conclusions to key stakeholders; Data management using SQL. Data manipulation and aggregation using Python. Propensity modeling using various ML algorithms. Text mining using NLP/AI techniques Propose solutions to the client based on gap analysis for the existing Telco platforms that can generate long term & sustainable value to the client. Gather business requirements from client stakeholders via interactions like interviews and workshops with all stakeholders Track down and read all previous information on the problem or issue in question. Explore obvious and known avenues thoroughly. Ask a series of probing questions to get to the root of a problem. Ability to understand the as-is process; understand issues with the processes which can be resolved either through Data & AI or process solutions and design detail level to-be state Understand customer needs and identify/translate them to business requirements (business requirement definition), business process flows and functional requirements and be able to inform the best approach to the problem. Adopt a clear and systematic approach to complex issues (i.e. A leads to B leads to C). Analyze relationships between several parts of a problem or situation. Anticipate obstacles and identify a critical path for a project. Independently able to deliver products and services that empower clients to implement effective solutions. Makes specific changes and improvements to processes or own work to achieve more. Work with other team members and make deliberate efforts to keep others up to date. Establish a consistent and collaborative presence with clients and act as the primary point of contact for assigned clients; escalate, track, and solve client issues. Partner with clients to understand end clients' business goals, marketing objectives, and competitive constraints. Storytelling Crunch the data & numbers to craft a story to be presented to senior client stakeholders. Professional & Technical Skills: Overall 10+ years of experience in Data Science B.Tech Engineering from Tier 1 school or Msc in Statistics/Data Science from a Tier 1/Tier 2 Demonstrated experience in solving real-world data problems through Data & AI Direct onsite experience (i.e., experience of facing client inside client offices in India or abroad) is mandatory. Please note we are looking for client facing roles. Proficiency with data mining, mathematics, and statistical analysis Advanced pattern recognition and predictive modeling experience; knowledge of Advanced analytical fields in text mining, Image recognition, video analytics, IoT etc. Execution level understanding of econometric/statistical modeling packages Traditional techniques like Linear/logistic regression, multivariate statistical analysis, time series techniques, fixed/Random effect modelling. Machine learning techniques like - Random Forest, Gradient Boosting, XG boost, decision trees, clustering etc. Knowledge of Deep learning modeling techniques like RNN, CNN etc. Experience using digital & statistical modeling software Python (must), R, PySpark, SQL (must), BigQuery, Vertex AI Proficient in Excel, MS word, Power point, and corporate soft skills Knowledge of Dashboard creation platforms Excel, tableau, Power BI etc. Excellent written and oral communication skills with ability to clearly communicate ideas and results to non-technical stakeholders. Strong analytical, problem-solving skills and good communication skills Self-Starter with ability to work independently across multiple projects and set priorities Strong team player Proactive and solution oriented, able to guide junior team members. Execution knowledge of optimization techniques is a good-to-have Exact optimization Linear, Non-linear optimization techniques Evolutionary optimization Both population and search-based algorithms Cloud platform Certification, experience in Computer Vision are good-to-haves Qualifications Experience: B.Tech Engineering from Tier 1 school or Msc in Statistics/Data Science from a Tier 1/Tier 2 Educational Qualification: B.tech or MSC in Statistics and Data Science

Skill required: Insight Engine - Analytics Insights Designation: Analytics and Modeling Analyst Qualifications: Any Graduation Years of Experience: 3 to 5 years What would you do? We are seeking a Machine Learning Data Scientist with 2 to 3 years of hands-on experience to join our growing Insights and Analytics team. The ideal candidate will be proficient in building ML models using supervised and unsupervised learning techniques, comfortable working with Python-based ML libraries, and experienced in data preparation workflows. Familiarity with Microsoft's AI/ML ecosystem is a strong advantage. What are we looking for? Preferred (Strong Advantage): Hands-on experience with Azure Machine Learning Studio and Automated ML. Familiarity with Azure Cognitive Services for vision, language, and decision tasks. Experience working with Microsoft Fabric and Synapse ML integration. Qualifications: Bachelor s or Master's degree in Computer Science, Data Science, Engineering, or related field. 2–3 years of experience in applied machine learning and data science projects. Solid understanding of model training, validation, and deployment workflows. Experience working with version control (e.g., Git) and collaborative development environments.Nice to Have: Familiarity with tools that help automate and manage the process of building, testing, and deploying machine learning models (MLOps and CI/CD pipelines). Basic understanding of cloud-based architecture and APIs. Roles and Responsibilities: Develop and implement machine learning models using supervised and unsupervised techniques. Apply appropriate machine learning algorithms for prediction tasks (e.g., linear regression, decision trees, neural networks) and data segmentation (e.g., k-means clustering, hierarchical clustering) based on project needs. Perform data preprocessing, feature engineering, and model evaluation. Use Python libraries such as scikit-learn, TensorFlow, and others to build and test models. Analyse and manipulate structured datasets using notebooks (e.g., Jupyter). Collaborate with data engineers, analysts, and product teams to translate business problems into ML solutions. Document model performance, data flows, and process pipelines. Qualification Any Graduation

Job Title - Data Scientist and Analytics Level 9:Consultant Ind & Func AI Decision Science Consultant S&C Management Level:09 - Consultant Location Bangalore/Gurgaon/Hyderabad/Mumbai Must have skills: Technical (Python, SQL, ML and AI), Functional (Data Scientist and B2B Analytics preferably in Telco and S&P industries) Good to have skills GEN AI, Agentic AI, cloud (AWS/Azure, GCP) Job Summary : About Global Network Data & AI:- Accenture Strategy & Consulting Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition About Comms & Media practice: The Accenture Center for Data and Insights (CDI) team helps businesses integrate data and AI into their operations to drive innovation and business growth by designing and implementing data strategies, generating actionable insights from data, and enabling clients to make informed decisions. In CDI, we leverage AI (predictive + generative), analytics, and automation to build innovative and practical solutions, tools and capabilities. The team is also working on building and socializing a Marketplace to democratize data and AI solutions within Accenture and for clients. Globally, CDI practice works across industry to develop value growth strategies for its clients and infuse AI & GenAI to help deliver top their business imperatives i.e., revenue growth & cost reduction. From multi-year Data & AI transformation projects to shorter more agile engagements, we have a rapidly expanding portfolio of hyper-growth clients and an increasing footprint with next-gen solutions and industry practices. Roles & Responsibilities: Experienced in Analytics in B2B domain. Responsible to help the clients with designing & delivering AI/ML solutions. He/she should be strong in Telco and S&P domain, AI fundamentals and should have good hands-on experience working with the following: Ability to work with large data sets and present conclusions to key stakeholders; Data management using SQL. Data manipulation and aggregation using Python. Propensity modeling using various ML algorithms. Text mining using NLP/AI techniques Propose solutions to the client based on gap analysis for the existing Telco platforms that can generate long term & sustainable value to the client. Gather business requirements from client stakeholders via interactions like interviews and workshops with all stakeholders Track down and read all previous information on the problem or issue in question. Explore obvious and known avenues thoroughly. Ask a series of probing questions to get to the root of a problem. Ability to understand the as-is process; understand issues with the processes which can be resolved either through Data & AI or process solutions and design detail level to-be state Understand customer needs and identify/translate them to business requirements (business requirement definition), business process flows and functional requirements and be able to inform the best approach to the problem. Adopt a clear and systematic approach to complex issues (i.e. A leads to B leads to C). Analyze relationships between several parts of a problem or situation. Anticipate obstacles and identify a critical path for a project. Independently able to deliver products and services that empower clients to implement effective solutions. Makes specific changes and improvements to processes or own work to achieve more. Work with other team members and make deliberate efforts to keep others up to date. Establish a consistent and collaborative presence with clients and act as the primary point of contact for assigned clients; escalate, track, and solve client issues. Partner with clients to understand end clients' business goals, marketing objectives, and competitive constraints. Storytelling Crunch the data & numbers to craft a story to be presented to senior client stakeholders. Professional & Technical Skills: Overall 8 years of experience in Data Science B.Tech Engineering from Tier 1 school or Msc in Statistics/Data Science from a Tier 1/Tier 2 Demonstrated experience in solving real-world data problems through Data & AI Direct onsite experience (i.e., experience of facing client inside client offices in India or abroad) is mandatory. Please note we are looking for client facing roles. Proficiency with data mining, mathematics, and statistical analysis Advanced pattern recognition and predictive modeling experience; knowledge of Advanced analytical fields in text mining, Image recognition, video analytics, IoT etc. Execution level understanding of econometric/statistical modeling packages Traditional techniques like Linear/logistic regression, multivariate statistical analysis, time series techniques, fixed/Random effect modelling. Machine learning techniques like - Random Forest, Gradient Boosting, XG boost, decision trees, clustering etc. Knowledge of Deep learning modeling techniques like RNN, CNN etc. Experience using digital & statistical modeling software Python (must), R, PySpark, SQL (must), BigQuery, Vertex AI Proficient in Excel, MS word, Power point, and corporate soft skills Knowledge of Dashboard creation platforms Excel, tableau, Power BI etc. Excellent written and oral communication skills with ability to clearly communicate ideas and results to non-technical stakeholders. Strong analytical, problem-solving skills and good communication skills Self-Starter with ability to work independently across multiple projects and set priorities Strong team player Proactive and solution oriented, able to guide junior team members. Execution knowledge of optimization techniques is a good-to-have Exact optimization Linear, Non-linear optimization techniques Evolutionary optimization Both population and search-based algorithms Cloud platform Certification, experience in Computer Vision are good-to-haves Qualifications Experience: B.Tech Engineering from Tier 1 school or Msc in Statistics/Data Science from a Tier 1/Tier 2 Educational Qualification: B.tech or MSC in Statistics and Data Science

Key Responsibilities: Leverage traditional machine learning techniques (decision trees, random forests, SVM, logistic regression) to build predictive models. Analyze complex datasets to identify key trends and provide data-driven insights for business decisions. Partner with cross-functional teams to understand business needs and translate them into effective ML solutions. Rigorously evaluate and optimize models for accuracy and real-world performance. Apply statistical and mathematical principles to enhance analytical outcomes. Communicate findings and model insights to both technical and non-technical stakeholders. Desired Skills and Qualifications: Deep understanding of traditional machine learning algorithms (decision trees, clustering, Naive Bayes, SVM, etc.). Strong proficiency in mathematics and statistics (linear algebra, probability, statistical inference). Proven ability to translate business problems into analytical frameworks and actionable insights. Expertise in data processing, cleaning, and feature engineering using Python (pandas, NumPy). Hands-on experience building and deploying ML models using Python and libraries like scikit-learn. Excellent analytical, problem-solving, and critical thinking skills. Strong communication and collaboration skills to effectively convey technical results. Familiarity with ML tools and frameworks (Scikit-learn, XGBoost, LightGBM). Experience with model evaluation, validation, and optimization techniques. Business acumen and the ability to apply ML to solve real-world business challenges. Preferred Qualifications: Bachelors or Masters degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field. 3+ years of experience as a Data Scientist with a focus on machine learning. Demonstrated experience in driving business decisions through data analysis and modeling. Familiarity with cloud platforms (AWS, Azure, GCP) for data science workflows.

About The Role The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. He/she must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, he/she must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates and supervisors. Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 5+ years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

About The Role The ideal candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The role enables to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 4 to 6 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

About The Role The ideal candidate must possess knowledge relevant to the functional area, and act as a subject matter expert in providing advice in the area of expertise, and also focus on continuous improvement for maximum efficiency. It is vital to focus on the high standard of delivery excellence, provide top-notch service quality and develop successful long-term business partnerships with internal/external customers by identifying and fulfilling customer needs. The candidate should be able to break down complex problems into logical and manageable parts in a systematic way, and generate and compare multiple options, and set priorities to resolve problems. The ideal candidate must be proactive, and go beyond expectations to achieve job results and create new opportunities. The role must positively influence the team, motivate high performance, promote a friendly climate, give constructive feedback, provide development opportunities, and manage career aspirations of direct reports. Communication skills are key here, to explain organizational objectives, assignments, and the big picture to the team, and to articulate team vision and clear objectives. Senior Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 7 to 10 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

About The Role The ideal candidate must possess knowledge relevant to the functional area, and act as a subject matter expert in providing advice in the area of expertise, and also focus on continuous improvement for maximum efficiency. It is vital to focus on the high standard of delivery excellence, provide top-notch service quality and develop successful long-term business partnerships with internal/external customers by identifying and fulfilling customer needs. The candidate should be able to break down complex problems into logical and manageable parts in a systematic way, and generate and compare multiple options, and set priorities to resolve problems. The ideal candidate must be proactive, and go beyond expectations to achieve job results and create new opportunities. The role must positively influence the team, motivate high performance, promote a friendly climate, give constructive feedback, provide development opportunities, and manage career aspirations of direct reports. Communication skills are key here, to explain organizational objectives, assignments, and the big picture to the team, and to articulate team vision and clear objectives. Senior Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 7 to 10 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

About The Role The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. He/she must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, he/she must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Process Manager Role and responsibilities: Collaborate with clients to understand their business objectives and provide analytic solutions that positively address their needs. Conduct discovery sessions, workshops and whiteboard sessions to identify, understand and define customer needs, objectives, roadmaps and/or business requirements to design solutions that can best address existing or prospective clients. Conducting stakeholder interviews and workshops to gather and prioritize business requirements. Analysing and documenting current business processes and systems. Identifying opportunities for process improvement, cost reduction, and efficiency gains. Translating business requirements into functional specifications for technical teams. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Collaborating with stakeholders to validate requirements and ensure alignment with business goals. Supporting the implementation and testing of solutions to ensure they meet business needs. Technical and Functional skills: 5 years of experience as a customer facing business analyst with minimum graduation in any field. Analytical ExpertiseProficient in analysing business processes, systems, and requirements to identify areas for improvement and optimization. Communication Skills: Ability to effectively communicate with stakeholders from various backgrounds to gather requirements, facilitate meetings, and present findings. Problem-Solving Skills: Capable of identifying problems, proposing solutions, and implementing strategies to address business challenges. DocumentationSkilled in documenting business requirements, user stories, process flows, and other artefact to ensure clear communication and understanding among stakeholders. Data AnalysisComfortable with data analysis techniques and tools to derive insights and make data-driven recommendations. Domain KnowledgePossesses a deep understanding of the Hi-tech industry or Supply chain / logistics domain, enabling them to provide valuable insights and recommendations. Project ManagementFamiliarity with project management methodologies and practices to effectively manage project timelines, resources, and deliverables. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Knowledge of data visualization tools like Power BI, Tableau, QlikSense etc. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Very high attention to detail and quality.