Data Analyst and Data science trainer

Data Science (SME)

FACE Prep is India’s leading employability and industry-aligned education company. For over 17 years, we have partnered with higher education institutions to bridge the gap between academia and industry.

● Worked with 2,000+ colleges and universities across India

● Trained 6+ million students across disciplines

● Market leaders in:

● Employability skills & placement readiness

● Industry-aligned academic papers(credit-bearing)

● Full-scale industry-aligned degree programs with universities

● Pan-India operations, headquartered in Coimbatore

● Young, energetic, mission-driven team

● Fast-growing organization with headcount expected to cross 1,000 employees in the next financial year

At FACE Prep, people are the platform on which outcomes are built.

Position: Data Science (SME)

Location: Coimbatore

Duration: Full-Time

Department: Training & Development

Experience: Minimum 2 Years

Role Description :

The Data Science Subject Matter Expert (SME) is a full-time, on-site role based in Coimbatore. The SME will design and deliver data science curricula, including lectures, hands-on labs, and project-based learning for students preparing for tech careers. Daily responsibilities include creating educational content, developing problem sets and case studies, mentoring learners on data analysis and model-building, and reviewing student work to provide constructive feedback. The SME will collaborate with other trainers and the product team to align content with current industry practices and hiring requirements. The role also involves analyzing learner performance data, refining teaching strategies, and occasionally contributing to workshops, bootcamps, and online learning materials.

Requirements:

• Strong foundation in Statistics and Data Science, with the ability to explain complex concepts clearly and practically.

• Hands-on experience in Data Analytics and Data Analysis, including working with real-world datasets and deriving actionable insights.

• Excellent Analytical Skills for problem-solving, designing assignments, and guiding learners through data-driven decision-making.

• Proficiency in common data science tools and languages (e.g., Python/R, SQL, data visualization tools such as Tableau/Power BI).

• Prior experience in teaching, mentoring, corporate training, or curriculum development is highly beneficial.

• Bachelor’s or Master’s degree in a quantitative field such as Computer Science, Statistics, Mathematics, Data Science, or related discipline.

• Ability to communicate effectively with diverse learner groups and collaborate within a multidisciplinary team.

• Exposure to machine learning concepts, model evaluation, and deployment practices is a plus.

IMMEDIATE JOINERS REQUIRED

At Nineleaps, we work on bleeding-edge technology with class-leading engineering practices on products that touch the lives of millions of users. We endeavor on doing things the right way, while also promoting a culture of excellence.

About the Role:

We are looking for a Data Analyst with strong analytical and problem-solving skills to transform complex data into meaningful, actionable business insights. The role involves working with large datasets, conducting deep-dive analysis, driving automation, and supporting data-driven product and business decisions.

Key Responsibilities:

• Analyse historical and large datasets to understand data sources, identify trends and patterns, and uncover meaningful insights.
• Write complex SQL queries and leverage Python to perform data analysis, ad hoc investigations, and solve business problems.
• Create reports and translate analytical findings into clear, concise, and actionable recommendations for stakeholders.
• Identify opportunities to drive automation and process improvements, improving efficiency and reducing manual effort.
• Communicate data-driven insights effectively to both technical and non-technical stakeholders in a clear and impactful manner.
• Maintain accurate documentation, ensure high-quality deliverables, and consistently meet defined timelines.

Requirements:

• 3–6 years of experience in Data Analytics, Business Intelligence, Data Engineering, or a similar analytical role.
• Strong hands-on expertise in Python and advanced SQL, with the ability to work with and analyse large datasets.
• Experience working with Google Sheets, and implementing automation through data pipelines or workflows.
• Strong analytical and problem-solving skills, with the ability to interpret complex data and derive actionable insights.
• Excellent communication skills with the ability to effectively present methods, results, and recommendations to stakeholders.
• Ability to collaborate effectively with remote and geographically distributed teams across different time zones.

Company Link: https://www.nineleaps.com/

Company LinkedIn: https://www.linkedin.com/company/nineleaps/

We are looking for a detail-oriented and analytical Data Analyst to join our team. The ideal candidate will be responsible for collecting, analyzing, and interpreting data to identify trends, generate insights, and support business decision-making.

The candidate should be comfortable working with large datasets, creating reports and dashboards, and communicating findings clearly to business stakeholders.

Key Responsibilities

• Collect, clean, organize, and analyze data from multiple sources.
• Identify trends, patterns, anomalies, and business opportunities from data.
• Create dashboards, reports, and visualizations for business teams.
• Track and report key performance indicators (KPIs).
• Perform ad-hoc analysis to support business and management decisions.
• Develop and maintain automated reports where possible.
• Work with stakeholders to understand reporting and analytical requirements.
• Ensure data accuracy, consistency, and quality.
• Present analytical findings in a clear and actionable manner.
• Maintain documentation for reports, dashboards, and data processes.

Strong Data Analyst Profile with Python, SQL, and data-pipeline expertise, ideally with retail / e-commerce datasets

2

Mandatory (Experience 1): Must have 4+ years of hands-on data-analyst experience, working with large datasets across areas such as sales, inventory, pricing, promotions, and customer behaviour.

3

Mandatory (Tech skill 1): Must have strong hands-on Python for data processing, transformation, automation, and analysis

4

Mandatory (Tech skill 2): Must have strong SQL skills, including complex queries, joins, aggregations, and data validation.

5

Mandatory (Tech skill 3): Must have a solid understanding of Data Lake architecture, ingestion, storage, and processing workflows

6

Mandatory (Tech skill 4): Must have hands-on experience with ETL / ELT pipelines, data integration, and transformation

7

Mandatory (Tech skill 5): Must have experience with Azure or GCP data services.

8

Mandatory (Tech skill 6): Must have understanding of or experience with Databricks and distributed data processing.

9

Mandatory (Tech skill 7): Must have knowledge of data modeling, data warehousing, and Lakehouse architecture

10

Mandatory (Tech skill 8): Must have experience with Power BI, Tableau, or Excel for reporting.

11

Mandatory (Communication): Must have strong analytical, documentation, and stakeholder-communication skills.

12

Mandatory (Education): Must hold a Bachelor’s degree in Computer Science, IT, Engineering, or a related field.

13

Mandatory (Note1): This is a 6-month contract role. Candidate must be comfortable with the contract engagement and able to join immediately (urgent — onboarding within ~a week)

Digital Mold Data Scientist and Manufacturing Analytics Specialist

Job Summary

COAST Systems is seeking a Data Scientist and Manufacturing Analytics Specialist in India to support a global client’s Digital Mold program.

This position will work with large and complex manufacturing, engineering, tooling, maintenance, and quality datasets. The successful candidate will transform fragmented operational data into reliable datasets, dashboards, actionable insights, and continuous-improvement opportunities.

This is a hands-on analytics role requiring close collaboration with engineering, manufacturing, operations, and business stakeholders. The position is particularly suited to someone who can understand a technical manufacturing problem, determine what the data is showing, and communicate practical recommendations that improve performance.

Key Responsibilities

• Collect, prepare, cleanse, normalize, and validate manufacturing and engineering data from multiple sources.
• Establish reliable and repeatable datasets for analytics, reporting, and decision-making.
• Analyze data to identify trends, risks, performance gaps, improvement opportunities, and potential cost savings.
• Develop and maintain dashboards, visualizations, KPI reporting, and business intelligence solutions.
• Analyze maintenance and operational performance using measures such as:
• Mean Time to Repair or MTTR
• Mean Time Between Failures or MTBF
• Overall Equipment Effectiveness or OEE
• Preventive and corrective maintenance performance
• Tool reliability, condition, quality, utilization, and lifecycle indicators
• Work closely with engineering and operations teams to convert technical and operational problems into data-driven solutions.
• Support continuous improvement, operational excellence, and process optimization initiatives.
• Align analyses and recommendations with client goals, priorities, and expected business outcomes.
• Identify relationships among tooling, maintenance, production, quality, sensor, and lifecycle data.
• Present findings clearly to technical and nontechnical stakeholders.
• Help establish consistent data definitions, analytical methods, and reporting standards.
• Support the development of predictive analytics, machine learning, and AI-enabled capabilities where appropriate.
• Learn the COAST software environment and relevant client or third-party systems.
• Help map and connect tool-specific data across systems so that information can be aligned and used consistently.

Required Qualifications

• Bachelor’s or master’s degree in data science, statistics, mathematics, computer science, engineering, operations research, or a related quantitative discipline.
• Strong data science and analytics experience involving large, complex, or multi-source datasets.
• Demonstrated experience with data preparation, cleansing, transformation, normalization, validation, and data-quality management.
• Strong statistical and analytical problem-solving skills.
• Proven experience developing dashboards, data visualizations, KPI reporting, and business intelligence solutions.
• Ability to analyze data and translate findings into clear, practical business or operational recommendations.
• Experience working with technical, engineering, operational, or business stakeholders.
• Strong continuous-improvement and process-optimization mindset.
• Ability to communicate clearly in English with global teams and client stakeholders.
• Ability to work independently, manage priorities, and investigate unclear or incomplete data.
• Strong attention to detail and commitment to data accuracy.

Preferred Qualifications

• Experience analyzing data in a manufacturing, engineering, maintenance, operations, or asset-management environment.
• Understanding of manufacturing equipment, tooling, maintenance, quality, and asset lifecycle concepts.
• Familiarity with MTTR, MTBF, OEE, preventive maintenance, reliability, and related manufacturing KPIs.
• Experience in plastics manufacturing or packaging, including any of the following:
• Injection molding
• Blow molding
• Extrusion blow molding
• Injection stretch blow molding
• Compression molding
• Other polymer-processing operations
• Experience working with cloud-based data platforms or data lake environments.
• Experience combining data from multiple software systems, databases, APIs, files, or vendor platforms.
• Experience with sensor, machine, equipment, IoT, or time-series data.
• Exposure to predictive analytics, machine learning, anomaly detection, forecasting, or AI applications.
• Experience developing analytics that lead to actionable workflows, reduced costs, improved reliability, or reduced manual effort.
• Experience supporting global organizations or working in a client-facing environment.

Technical Skills

Candidates should demonstrate proficiency in several of the following areas:

• SQL
• Python or R
• Statistical analysis
• Data preparation and transformation
• Data validation and data-quality analysis
• Dashboard and visualization development
• Power BI, Tableau, QuickSight, or a comparable BI platform
• Cloud data lakes or cloud analytics environments
• Relational and non-relational data sources
• Advanced Microsoft Excel
• Predictive modeling or machine learning
• API or multi-system data integration

Specific experience with every listed technology is not required. The candidate must, however, have strong foundational analytics skills and the ability to learn unfamiliar platforms and data environments.

Critical Competencies

• Analytical curiosity
• Structured problem-solving
• Systems thinking
• Data accuracy and attention to detail
• Continuous-improvement mindset
• Business and operational awareness
• Clear written and verbal communication
• Cross-functional collaboration
• Client responsiveness
• Adaptability and willingness to learn
• Ability to convert analysis into action

Experience

Approximately 4 to 8 years of relevant professional experience is preferred. Candidates with fewer years may be considered if they demonstrate strong hands-on analytics experience, manufacturing exposure, and the ability to work directly with engineering and operational stakeholders.

What Success Looks Like

The successful candidate will:

• Create trusted and repeatable manufacturing datasets.
• Deliver dashboards and reports that stakeholders actively use.
• Identify meaningful risks, trends, and improvement opportunities.
• Help engineering and operations teams make better decisions from their data.
• Improve the consistency of tool-specific information across systems.
• Progressively develop more advanced predictive and AI-enabled Digital Mold capabilities.
• Produce measurable improvements in reliability, operational performance, cost, and efficiency.

Suggested Key Skills

Data Science, Manufacturing Analytics, Data Analytics, Business Intelligence, Dashboard Development, Data Visualization, Power BI, Tableau, Amazon QuickSight, SQL, Python, R, Statistical Analysis, Data Cleansing, Data Normalization, Data Validation, Data Quality, Manufacturing KPI, OEE, MTTR, MTBF, Predictive Analytics, Machine Learning, Continuous Improvement, Process Optimization, Maintenance Analytics, Reliability Analytics, Cloud Data Lake, Sensor Data, IoT Analytics, Injection Molding, Plastics Manufacturing

Key Responsibilities

 Strong understanding of Machine Learning algorithms (supervised and unsupervised)

 Hands-on experience with Deep Learning frameworks (TensorFlow, PyTorch, or similar)

 Experience in NLP techniques and libraries (NLTK, spaCy, Hugging Face, etc.)

 Solid knowledge of Statistics, probability, and data analysis methods

 Proficiency in SQL for querying relational databases

 Strong programming skills in Python (or similar languages)

 Excellent communication skills with the ability to explain complex concepts simply

Required Qualifications

 3+ years of hands-on experience as a Data Scientist or in a similar role.

 Strong expertise in classical machine learning and regression modeling.

 Solid understanding of statistics, including probability, distributions, hypothesis testing,

and correlation analysis.

 Proficiency in Python with libraries such as: scikit-learn pandas NumPy

 Experience working with structured/tabular data.

 Strong problem-solving and analytical thinking skills.

 Ability to clearly explain models and results to non-technical stakeholders.

About the Company: 

WebMD Health Corp., an Internet Brands Company, is the leading provider of health information services, serving patients, physicians, health care professionals, employers, and health plans through our public and private online portals, mobile platforms, and health-focused publications. The WebMD Health Network includes WebMD Health, Medscape, Jobson Healthcare Information, prIME Oncology, MediQuality, Frontline, QxMD, Vitals Consumer Services, MedicineNet, eMedicineHealth, RxList, OnHealth, Medscape Education, and other owned WebMD sites. WebMD®, Medscape®, CME Circle®, Medpulse®, eMedicine®, MedicineNet®, theheart.org®, and RxList® are among the trademarks of WebMD Health Corp. or its subsidiaries. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.

For Company details, visit our website: www.webmd.com

Experience: 3+ years

Qualification: Master's degree in Computer Science, Statistics, Mathematics, or a related field.

Work Timings: 2 PM to 11 PM IST

Position Requirement:

• Write clean and efficient code in Python and/or R for data analysis, statistical modeling, and machine learning tasks.
• Apply statistical and machine learning techniques to analyze large datasets and extract meaningful patterns, trends, and insights. Develop and implement predictive models for various business applications.
• Formulate hypothesis tests and design experiments to validate assumptions, measure the impact of changes, and optimize decision-making processes.
• Demonstrate strong SQL skills for efficient data querying and manipulation using window functions.
• Work with large datasets and ensure data quality and accuracy.
• Experience with dashboarding tools like Tableau is a plus to visualize and present data-driven insights to both technical and non-technical stakeholders.
• Ability to communicate complex technical concepts and insights in a clear and concise manner to both technical and non-technical audiences. Engage with the leadership team and clients to understand business requirements and provide data-driven solutions.
• Work with real world case studies in Data Science and a chance to implement various modelling techniques. Opportunity to independently execute and lead analytical projects and assignments.
• Help solve some challenging Healthcare related digital marketing problems globally. Transform business question into data requirements; collect and merge the data; analyse the data, link it to the business reality and present the results
• Develop predictive models and machine learning algorithms to study change in physician prescribing behaviour as well as WebMD integrated campaign response behaviour. Build analysis to understand user engagement and behaviours across various WebMD products.

Technical Skills needed:

1.Experience with data manipulation in SQL environment is a must. Experience with BigQuery/Vertica data warehousing is good to have

• Experience with statistical and data manipulation tools such as Python or R is a must 
• Need very good expertise in using Microsoft Excel, and Microsoft PowerPoint. Excellent presentation skills required
• Experience developing statistical models like hypothesis testing, regression models, classifications models, forecasting etc is a must 
• Algorithm designing and implementation skills in R or Python is required 

Requirements

• B.Tech/B.E. / MSc Statistics from premier institutes with
• Minimum 80% marks in 10th and 12th
• Minimum 75% marks in graduation
• 2-5 years of relevant work experience in analytics field
• Proven experience in data science, statistical modeling, and machine learning applications.
• Strong proficiency in Python and/or R programming languages.
• Solid understanding of statistical concepts, hypothesis testing, and experimental design
• Expertise in SQL for data querying and manipulation.
• Familiarity with dashboarding tools is a plus.
• Excellent presentation, communication and interpersonal skills.

We’re looking for a dynamic and driven Data Analyst to join our team of technology enthusiasts. This role is crucial in transforming data into insights that support strategic decision-making and innovation within the insurance technology (InsurTech) space. If you’re passionate about working with data, understanding systems, and delivering value through analytics, we’d love to hear from you.

What We’re Looking For

• Proven experience working as a Data Analyst or in a similar analytical role
• 5+ Years of experience in the field
• Strong command of SQL for querying and manipulating relational databases
• Experience with Power BI for building impactful dashboards and reports
• Familiarity with QlikView and Qlik Sense is a plus
• Ability to communicate findings clearly to technical and non-technical stakeholders
• Knowledge of Python or R for data manipulation is nice to have
• Bachelor’s degree in Computer Science, Statistics, Mathematics, Economics, or a related field
• Understanding of the insurance industry or InsurTech is a strong advantage

What You’ll Be Doing:

• Delivering timely and insightful reports to support strategic decision-making
• Working extensively with Policy Administration System (PAS) data to uncover patterns and trends
• Ensuring data accuracy and consistency across reports and systems
• Collaborating with clients, underwriters, and brokers to translate business needs into data solutions
• Organizing and structuring datasets, contributing to data engineering workflows and pipelines
• Producing analytics to support business development and market strategy

Hiring for Data Scientist / Senior Data Scientist

Exp : 4 - 12 yrs

Edu : BE/B.tech/MCA

Work Location : Pune

Notice Period : Immediate - 15 days

Skills :

4+ years of experience in data engineering, data science, or related domains.

Hands-on experience with SQL, Python, and distributed data systems.

Knowledge of machine learning techniques and statistical analysis.

Experience with cloud data platforms (Azure Data Factory, AWS Glue, GCP BigQuery).

Familiarity with DevOps practices and CI/CD for data pipelines.

Platforms & Operations Experience (Preferred)

- Experience working with Azure, AWS, or Google Cloud data tools.

Operational experience with data orchestration tools (Airflow, ADF, Glue).

Understanding of Kubernetes, Docker, or containerized environments.

Hands-on experience with data warehousing platforms (Snowflake, Redshift, BigQuery).

Experience in monitoring, logging, and alerting operations for data workflows.

🚀 We’re Hiring | Data Scientist 🧠📊

Ready to turn data into real-world intelligence? Join us and work on exciting AI/ML & data-driven solutions!

🔹 Experience: 8+ Years

🔹 Must-Have Skills:

🐍 Python | 🤖 Machine Learning | ☁️ Cloud | 🧠 NLP | 📊 Data Visualization

📍 Location: Pune

💼 Work Mode: Work from Office

If you're passionate about Data Science, AI & solving complex business problems, we’d love to hear from you!

📩 Interested? Kindly text

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