Account Manager (Analytics) - KiE Square is seeking a motivated and results-driven Account Manager to join our dynamic team.- The ideal candidate will act as the primary point of contact for clients, ensuring strong relationships and satisfaction while helping them achieve their business goals through data-driven insights and analytics solutions. The Account Manager will be responsible for understanding client needs, managing projects, and working cross-functionally with internal teams to deliver high-quality solutions. Key Responsibilities: - Client Relationship Management: Serve as the main liaison between the company and clients, maintaining strong relationships and ensuring client satisfaction.- Client Retention & Growth: Identify opportunities to enhance client engagements through upselling/cross-selling new analytics solutions, services, and technologies.- Project Management: Oversee the delivery of analytics projects, ensuring they meet client expectations in terms of quality, timelines, and scope.- Needs Assessment: Work closely with clients to understand their business challenges and analytics requirements, providing customized recommendations and solutions.- Collaboration with Internal Teams: Work with data scientists, analysts, and other technical teams to deliver projects on time and within budget.- Reporting & Insights: Present findings, reports, and recommendations to clients, translating complex data analytics into actionable business insights.- Contract Negotiations & Renewals: Handle contract renewals and assist in negotiating terms that benefit both the client and the company.- Performance Monitoring: Track key metrics and client satisfaction to ensure client success and identify areas for improvement. Requirements: - Education: Master's degree in Business, Marketing, Data Science, or a related field.- Experience: 4+ years of experience in account management, preferably in the analytics, data, or technology sector.- Analytical Skills: Ability to understand data-driven insights and communicate their business impact effectively.- Project Management: Proven experience in managing multiple projects simultaneously with attention to detail and meeting deadlines.- Communication Skills: Excellent written and verbal communication skills with the ability to present complex information clearly.- Client-Focused: Strong client service skills with a solution-oriented mindset and the ability to manage relationships across varying levels of seniority.- Tech-Savvy: Proficiency in analytics platforms, data visualization tools (e.g., Tableau, Power BI), CRM software, and Microsoft Office Suite.Preferred Qualifications:- Experience working in a consulting or analytics firm.- Familiarity with advanced data analytics techniques such as predictive modeling, machine learning, or AI.- Knowledge of industry-specific analytics solutions (e.g., financial, CPG/Retail, healthcare).
Identify and generate new B2B leads through various channels including email campaigns, LinkedIn outreach, cold calling, web research, and Maintain and manage lead data in the CRM system and ensure accurate reporting of lead generation activities.
Identify and generate new B2B leads through various channels including email campaigns, LinkedIn outreach, cold calling, web research, and Maintain and manage lead data in the CRM system and ensure accurate reporting of lead generation activities.
JD- Research and identify potential customers for our analytics product across industries. Generate leads from LinkedIn outreach, cold calling, and targeted campaigns. Engage with (CXOs, Analytics Managers, IT Heads) to create interest.
the Bachelor's Role Overview- KiE Square Analytics is seeking a motivated Lead Generation Executive to help expand our customer base for our analytics product. This role is ideal for freshers or early-career professionals eager to grow in B2B sales and gain hands-on experience in the analytics product industry. Key Responsibilities Research and identify potential customers for our analytics product across industries. Generate qualified leads through LinkedIn outreach and targeted campaigns. Engage with decision-makers (CXOs, Analytics Managers, IT Heads) to create interest. Maintain and update CRM with lead information and outreach status. Coordinate with sales team to schedule product demos and discussions. Share client feedback with product and marketing teams to improve positioning. Required Skills & Qualifications Bachelors degree in Business, Marketing, IT, or related field. 01 year experience in lead generation/inside sales. (internships count). Excellent communication and interpersonal skills. Basic knowledge of analytics or cloud products (preferred, not mandatory). Familiarity with LinkedIn, CRM tools, and Excel. Goal-oriented, self-driven, and eager to learn sales in the product domain.
KiE Square is seeking a highly skilled Senior Full Stack Data Engineer with a strong background in analytics consulting. The ideal candidate must have hands-on experience designing and implementing robust data architectures, building scalable data pipelines, and enabling analytics and machine learning solutions for business impact. This role requires a blend of technical expertise, solution design capability, and business understanding to support analytical consulting projects across diverse industries. You will work closely with data scientists, BI developers, and client teams to ensure high-quality, production-ready data environments and insights delivery. Key Responsibilities Design, develop, and maintain end-to-end data pipelines from multiple data sources (structured & unstructured). Build and optimise data architectures, ETL/ELT processes, and data models to support analytics and ML initiatives. Collaborate with data scientists and analysts to operationalise predictive and prescriptive solutions. Develop APIs and microservices for data consumption and integration with analytics applications. Partner with consulting teams to translate business problems into scalable data solutions. Implement data quality, governance, and security best practices. Drive cloud data migration and modernisation initiatives (AWS, Azure, or GCP). Lead performance optimisation and monitoring of data infrastructure. Mentor junior engineers and contribute to data engineering best practices within the team. Required Skills & Qualifications Education: Bachelors or Masters degree in Computer Science, Information Systems, Engineering, or related field. Experience: 57 years of hands-on experience in data engineering, preferably in an analytics consulting environment. Strong proficiency in Python, SQL, and data pipeline frameworks (e.g., Airflow, Prefect, or Luigi). Familiarity with API development (Flask/FastAPI) and containerization (Docker, Kubernetes). Expertise with data warehousing (Snowflake, Redshift, Big Query, Databricks, or Synapse). Hands-on experience with cloud platforms – AWS / Azure / GCP (any one is mandatory). Deep understanding of ETL/ELT design patterns, data modelling (Star/Snowflake), and schema design. Working knowledge of big data technologies (Spark, Hadoop, Kafka). Exposure to CI/CD pipelines, Git-based workflows, and MLOps/DataOps practices. Strong problem-solving ability and client communication skills.
KiE Square is looking for a passionate and experienced Sr. Data Scientist to join our Analytics Consulting team. The ideal candidate shall possess a strong blend of technical expertise, analytical thinking, and business consulting skills. You will be responsible for developing and deploying scalable machine learning solutions, building end-to-end data pipelines, and translating analytical insights into actionable business strategies for our clients. Responsibilities Partner with clients to understand business challenges and identify data-driven opportunities. Design, build, and deploy end-to-end machine learning models and analytical solutions tailored to client objectives. Develop data ingestion, transformation, and modelling pipelines using modern data engineering tools. Translate analytical outcomes into clear business insights, dashboards, and recommendations. Work closely with consulting teams to integrate analytics into decision-making frameworks. Build and maintain production-ready APIs and ML workflows for scalable model deployment. Implement MLOps practices for continuous integration, deployment, and performance monitoring. Mentor junior team members and contribute to internal best practices in analytics and data science. Required Skills & Qualifications Education: B.Tech/M.Tech in Computer Science (with Data Science Masters is a plus) Experience: 57 years in analytics consulting, applied data science, or end-to-end AI/ML solution development. Proven experience in problem framing, model development, and production deployment. Proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, etc.) and SQL. Hands-on experience on at least two of the top platforms such as Google Vertex AI, Amazon Sagemaker, Azure Databaricks. Proficiency with SaaS LLMs, including Lang chain, llama index, vector databases, Prompt engineering (COT, TOT, ReAct, agents). Hands-on experience with data engineering tools (Airflow, Spark, or Databricks). Techniques such as quantization, LLM finetuning using PEFT, RLHF, data annotation workflow, and GPU utilization. Exposure to cloud environments such as AWS, Azure, or GCP. Ability to analyse structured and unstructured data from multiple sources. Experience in model interpretability, A/B testing, and business impact measurement. Strong client communication, storytelling, and presentation skills. Good to Have Exposure to data visualization tools such as Power BI, Tableau, AWS Quicksight or Looker. Understanding of consulting frameworks and client delivery models. Familiarity with API development (Flask, FastAPI) and containerization (Docker, Kubernetes). Experience with LLMs or Generative AI use cases is a plus.