Candidates willing to learn alternates can apply Data Scientist Data Analyst Data Engineers Collect, clean, and preprocess structured and unstructured datasets. Perform exploratory data analysis (EDA) to identify patterns, trends, and insights. Assist in building and testing machine learning models under the guidance of senior team members. Generate reports, dashboards, and visualizations using tools such as Tableau, Power BI, or Matplotlib . Work with cross-functional teams (business, engineering, product) to support data-driven decision-making. sr professionals Collect, clean, and transform large-scale datasets from multiple sources. Perform exploratory data analysis (EDA) to uncover trends, patterns, and actionable insights. Build, validate, and deploy machine learning models (classification, regression, recommendation, NLP, deep learning). Collaborate with data engineers to ensure data availability, scalability, and quality. Work closely with business and product teams to define problems, identify opportunities, and provide data-driven recommendations. Develop and maintain dashboards, reports, and visualization tools (Tableau, Power BI, or similar). Stay updated with latest ML/AI research, tools, and frameworks to improve existing solutions. Document workflows, models, and results for reproducibility and knowledge sharing. Data Engineer will manage data pipelines, write optimized SQL queries, automate data processing tasks using Python, and ensure data accuracy and integrity through collaboration and automated testing. Responsibilities also include overseeing data governance and compliance.
Role & responsibilities Collect and clean data from multiple sources. Perform exploratory data analysis (EDA) to find patterns and insights. Build and validate predictive/machine learning models. Apply statistical methods to test hypotheses and measure outcomes. Translate business problems into data-driven solutions. Visualize results using dashboards and reports. Communicate findings to technical and non-technical stakeholders. Collaborate with engineers, analysts, and business teams. Deploy and optimize models in production. Stay updated with new tools, frameworks, and research Preferred candidate profile Any candidate 0-5 yrs exp can apply
Job Description: We are looking for a motivated and disciplined professional to join our team. The ideal candidate will have hands-on experience in email marketing, digital marketing, and customer interaction. This role requires strong communication skills, confidence, and the ability to quickly learn new tools and techniques. Key Responsibilities: Plan and execute email marketing campaigns to engage and retain customers Manage digital marketing activities across multiple channels Meet with customers to understand their needs and provide suitable solutions Maintain strong communication and build long-term relationships with clients Continuously learn and adapt to new digital marketing trends and tools Ensure discipline and responsibility in meeting assigned goals and deadlines Requirements: Proven experience in email marketing and digital marketing Strong communication and interpersonal skills Confidence and a proactive attitude Ability to learn and adapt quickly to new technologies Willingness to work from the office at least 8 days per month (remaining days remote) Highly disciplined and serious about professional responsibilities Work Mode: Hybrid Minimum 8 days in office per month, remaining period work from home Who Can Apply: Candidates who are disciplined, responsible, and serious about building a career in digital marketing and customer engagement.
Core Technical Skills Programming: Python (Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn), R Databases & Querying: SQL, NoSQL (MongoDB) Machine Learning: Regression, Classification, Clustering, Ensemble Methods, Feature Engineering, Model Evaluation Deep Learning: TensorFlow, Keras, PyTorch (for trainers in advanced AI topics) Data Visualization & BI Tools: Power BI, Tableau, Excel (advanced functions, dashboards) Big Data Tools (optional for advanced training): Spark, Hadoop Cloud Platforms: AWS, Azure, GCP (basic ML and data handling services) MLOps (optional advanced): Git/GitHub, Docker, MLflow 2. Statistics & Mathematics Descriptive & Inferential Statistics Probability & Distributions Hypothesis Testing & A/B Testing Linear Algebra & Calculus (for ML/DL concepts) Time Series Analysis 3. Teaching & Training Skills Curriculum Design & Content Development Creating structured learning paths, modules, and hands-on labs Instructional Delivery – Classroom, virtual, and corporate training methods Simplifying Complex Concepts – Explaining technical topics in beginner-friendly ways Assessment & Feedback – Designing quizzes, assignments, projects, and providing constructive feedback Men
Key Responsibilities: Analyze large datasets to discover trends, patterns, and actionable insights Work on projects services if you want to join products Build predictive models and machine-learning algorithms to solve real-world business problems Work closely with business stakeholders to identify opportunities for leveraging company data Design and implement A/B tests and statistical analyses to evaluate strategies What We Offer: Competitive salary and benefits Flexible work environment Opportunities for professional development and growth A collaborative and inclusive team culture
Key Responsibilities: Analyze large datasets to discover trends, patterns, and actionable insights Work on projects services if you want to join products Build predictive models and machine-learning algorithms to solve real-world business problems Work closely with business stakeholders to identify opportunities for leveraging company data Design and implement A/B tests and statistical analyses to evaluate strategies What We Offer: Competitive salary and benefits Flexible work environment Opportunities for professional development and growth A collaborative and inclusive team culture
Revenue Generation Identify, source, and recruit potential candidates including career transitioners , freshers , and entry-level professionals . Conduct outreach programs across colleges, universities, and corporate campuses to attract and engage potential candidates. Organize and participate in field events , career fairs, and information sessions to promote training and placement programs. 2. Training Coordination Facilitate enrollment of selected candidates into structured training programs tailored to industry requirements. Monitor and track candidate progress throughout the training period, ensuring performance metrics are met. 3. Marketing & Promotion Plan and execute marketing strategies (offline and online) to attract qualified leads. Coordinate digital and field marketing campaigns to increase visibility and reach among target audiences. 4. Placement Support Work with internal placement teams and industry partners to secure job opportunities for trained candidates. Track prevenue enhancement